JP4414464B2 - Visual processing device, visual processing method, visual processing program, and semiconductor device - Google Patents

Description

  The present invention relates to a visual processing device, and more particularly to a visual processing device that performs gradation processing of an image signal. The present invention also relates to a visual processing method, a visual processing program, and a semiconductor device.

As visual processing of an image signal of an original image, spatial processing and gradation processing are known.
Spatial processing is to perform processing of a target pixel using pixels around the target pixel to be processed. Further, a technique for performing contrast enhancement of an original image, dynamic range (DR) compression, or the like using a spatially processed image signal is known. In contrast enhancement, the difference between the original image and the blur signal (sharp component of the image) is added to the original image to sharpen the image. In DR compression, a part of the blur signal is subtracted from the original image, and dynamic range compression is performed.
The gradation processing is processing for converting pixel values using a lookup table (LUT) or the like for each target pixel regardless of the surrounding pixels of the target pixel, and is sometimes called gamma correction. For example, when contrast enhancement is performed, pixel values are converted using an LUT that enhances gradations having a high gradation frequency in the original image. As gradation processing using the LUT, gradation processing (histogram equalization method) that determines and uses one LUT for the entire original image, and determines and uses the LUT for each of the image areas obtained by dividing the original image into a plurality of parts. Gradation processing (local histogram equalization method) is known (for example, refer to Patent Document 1).

With reference to FIGS. 33 to 36, a description will be given of the gradation processing for determining and using the LUT for each of the image regions obtained by dividing the original image into a plurality of parts.
FIG. 33 shows a visual processing device 300 that determines and uses an LUT for each of image areas obtained by dividing an original image into a plurality of parts. The visual processing device 300 divides an original image input as the input signal IS into a plurality of image regions Sm (1 ≦ m ≦ n: n is the number of divisions of the original image), and each image region Sm. A gradation conversion curve deriving unit 310 for deriving a gradation conversion curve Cm, and a gradation processing unit for loading the gradation conversion curve Cm and outputting an output signal OS obtained by performing gradation processing on each image region Sm 304. The gradation conversion curve deriving unit 310 creates a lightness histogram Hm in each image area Sm, and a floor for creating a gradation conversion curve Cm for each image area Sm from the created lightness histogram Hm. And an adjustment curve creation unit 303.

The operation of each part will be described with reference to FIGS. The image dividing unit 301 divides the original image input as the input signal IS into a plurality (n) of image regions (see FIG. 34A). The histogram creation unit 302 creates a brightness histogram Hm for each image region Sm (see FIG. 35). Each brightness histogram Hm shows the distribution state of brightness values of all pixels in the image area Sm. That is, in the brightness histogram Hm shown in FIGS. 35A to 35D, the horizontal axis indicates the brightness level of the input signal IS, and the vertical axis indicates the number of pixels. The gradation curve creation unit 303 accumulates the “number of pixels” of the brightness histogram Hm in the order of brightness, and sets this accumulated curve as the gradation conversion curve Cm (see FIG. 36). In the gradation conversion curve Cm shown in FIG. 36, the horizontal axis indicates the brightness value of the pixel in the image area Sm in the input signal IS, and the vertical axis indicates the brightness value of the pixel in the image area Sm in the output signal OS. The gradation processing unit 304 loads the gradation conversion curve Cm and converts the brightness value of the pixel in the image area Sm in the input signal IS based on the gradation conversion curve Cm. By doing so, the gradient of the frequently occurring gradation is set in each block, and the sense of contrast for each block is improved.
JP 2000-57335 A (page 3, FIGS. 13 to 16)

The histogram creation unit 302 creates a gradation conversion curve Cm from the brightness histogram Hm of the pixels in the image area Sm. In order to more appropriately create the gradation conversion curve Cm to be applied to the image area Sm, it is necessary to have all the pixels from the dark part (shadow) to the bright part (highlight) of the image. Need to refer to. For this reason, each image area Sm cannot be made very small, that is, the original image division number n cannot be made too large. The division number n varies depending on the image content, but empirically, a division number of 4 to 16 is used.
Since each image area Sm cannot be made very small, the following problem may occur in the output signal OS after gradation processing. That is, since gradation processing is performed using one gradation conversion curve Cm for each image region Sm, the boundary of the boundary of each image region Sm is unnaturally noticed, or a pseudo contour is generated in the image region Sm. There is a case. In addition, since the image area Sm is large when the number of divisions is 4 to 16 at most, when there are extremely different images between the image areas, the shading change between the image areas is large, and it is difficult to prevent the occurrence of the pseudo contour. For example, as shown in FIGS. 34 (b) and 34 (c), the density changes extremely depending on the positional relationship between the image (for example, an object in the image) and the image region Sm.

  Accordingly, an object of the present invention is to provide a visual processing device that realizes gradation processing that further improves the visual effect.

A first invention is a visual processing device including an image dividing unit, a selection signal deriving unit, and a gradation processing unit. The image dividing unit divides the input image into a plurality of image areas. The selection signal deriving unit uses the feature parameters of the wide-area image region including at least a plurality of image regions around the target image region to be subjected to gradation processing in the image region, and performs gradation conversion applied to the target image region. A selection signal for selecting a curve is determined. The gradation processing unit inputs an input signal that is a pixel value included in the target image region and a selection signal, and performs gradation processing on the input signal using a gradation conversion curve.
2nd invention is 1st invention, Comprising: A wide area | region image area | region is an area | region including 5 or more image areas in a vertical direction and 5 or more image areas in a horizontal direction centering | focusing on an object image area | region.
3rd invention is 1st or 2nd invention, Comprising: An image division part divides | segments input image data into image data larger than "16".

4th invention is 1st invention, Comprising: A wide area | region image area | region is an image area | region around the target image area | region which does not contain a target image area | region.
The fifth invention is any one of the first to fourth inventions, wherein the characteristic parameter is an average brightness value of the wide area image region.
The sixth invention is the fifth invention, wherein the selection signal deriving unit derives the average brightness for each of the divided image areas, and derives the average brightness from the plurality of average brightness.
The seventh invention is the sixth invention, wherein the selection signal deriving unit reduces the weighting to an average brightness of an image area having an average brightness value significantly different from the average brightness value of the target image area, or “0”. The average brightness of the wide area image area is derived as follows.
The eighth invention is any one of the first to fourth inventions, wherein the selection signal deriving unit derives the feature data for each of the divided image areas, and the feature data that is significantly different from the feature data of the target image area The feature parameter of the wide area image area is derived by setting the weighting to be small or “0” for the characteristic data of the image area having.

A ninth invention is any one of the first to fourth inventions, wherein the selection signal deriving unit derives the feature data for each of the divided image areas, and the image area is separated from the target image area. For the feature data, the feature parameter of the wide area image area is derived with a small weight or “0”.
A tenth aspect of the invention is any one of the first to ninth aspects of the invention, and further includes a selection signal correction unit that corrects the selection signal determined for the target image area in units of pixels.
The eleventh invention is the tenth invention, wherein the selection signal correction unit sets a plurality of image areas around the target image area as a temporary target image area for performing only selection signal determination, and sets the temporary target image. Each selection signal determined by the feature parameter of the wide area image area with respect to the area is obtained, and each of the selection signals determined for the provisional target image area and the target image area is determined by the position coordinates of the pixels included in the target image area. By performing the internal division, the selection signal determined for the target image area in the previous period is corrected in units of pixels.

A twelfth aspect of the invention is any one of the first to eleventh aspects of the invention, wherein the gradation processing unit receives a selection signal and outputs a gradation processing signal, and a gradation processing signal. And a tone correction unit that outputs an output signal in which the tone is corrected.
A thirteenth invention is any one of the first to twelfth inventions, wherein the gradation processing unit inputs a plurality of selection signals for peripheral image areas including the target image area, and a plurality of gradation processing signals. And a gradation correction unit that outputs an output signal in which gradation is corrected according to the position of the pixel included in the target image region using a plurality of gradation processing signals.
A fourteenth invention is a visual processing device including an image dividing unit, a gradation conversion characteristic deriving unit, and a gradation processing unit. The image dividing unit extracts the first region from the input image data. The gradation conversion characteristic deriving unit determines conversion characteristics of a plurality of pixel values included in the first area using at least image data of the peripheral image area for the first area or data derived from the image data. The gradation processing unit performs gradation conversion on the target pixel included in the first area based on conversion characteristics.

A fifteenth aspect of the invention is the fourteenth aspect of the invention, wherein the conversion characteristics of the pixel values of the pixels included in the second area adjacent to the first area are used for determining the conversion characteristics of the first area. This is determined using the pixel value of a new peripheral image area having pixels that overlap the image area.
In a sixteenth aspect based on the fourteenth aspect, the gradation conversion characteristic deriving unit converts the conversion characteristic of the plurality of pixel values included in the first area into the image data of the peripheral image area of the first area. Determined using sampling data.
A seventeenth aspect of the invention is a visual processing device that includes an image dividing unit, a gradation conversion characteristic deriving unit, and a gradation processing unit. The image dividing unit divides input image data into a plurality of image regions. The gradation conversion characteristic deriving unit sets a wide area image area including a plurality of image areas around the target image area Pm, which is an image area including the processing target pixel, and uses image data of the wide area image area including the target image area. The gradation conversion characteristics of the target image area are determined. The gradation processing unit performs gradation conversion of the target pixel included in the target image region using the gradation conversion characteristic.

An eighteenth aspect is the seventeenth aspect, wherein the gradation conversion characteristic deriving unit includes at least five image areas in the vertical direction and five or more image areas in the horizontal direction, with the target image area as a center. A wide image area is set using.
The nineteenth invention is the seventeenth or eighteenth invention, wherein the image data is a brightness histogram of a wide area image region.
The twentieth invention is the invention according to any one of the seventeenth to twentieth inventions, wherein the gradation conversion characteristic deriving unit is applied to the target image region from the histogram creating unit that creates the brightness histogram of the wide area image region. A gradation curve creating unit that creates a gradation conversion curve to be performed.
A twenty-first invention is a gradation processing method used in a visual processing device, and includes a step of dividing an input image into a plurality of image regions, a step of determining a selection signal, and a step of gradation processing. . The step of determining the selection signal includes a plurality of image areas around the target image area to be subjected to gradation processing in the image area, and using the feature parameters of the wide area image area including or not including the target image area. Then, a selection signal for selecting a gradation conversion curve to be applied to the target image area is determined. In the gradation processing step, an input signal that is a pixel value included in the target image region and a selection signal are input, and the input signal is subjected to gradation processing using a gradation conversion curve.

A twenty-second invention is a program for causing a computer to execute a step of dividing an input image into a plurality of image regions, a step of determining a selection signal, a step of gradation processing. In the step of determining the selection signal, a plurality of image areas around the target image area to be subjected to gradation processing among the image areas are used, and feature parameters of the wide area image area including or not including the target image area are used. Then, a selection signal for selecting a gradation conversion curve to be applied to the target image area is determined. In the gradation processing step, an input signal that is a pixel value included in the target image region and a selection signal are input, and the input signal is subjected to gradation processing using a gradation conversion curve.
A twenty-third invention is a semiconductor device used in a visual processing device, and executes processing for dividing an input image into a plurality of image regions, processing for determining a selection signal, and processing for gradation processing. In the process of determining the selection signal, a plurality of image areas around the target image area to be subjected to the gradation process among the image areas are used, and feature parameters of the wide area image area including or not including the target image area are used. Then, a selection signal for selecting a gradation conversion curve to be applied to the target image area is determined. In the gradation processing, an input signal that is a pixel value included in the target image area and a selection signal are input, and the input signal is subjected to gradation processing using a gradation conversion curve.

  The visual processing device of the present invention makes it possible to realize gradation processing that further improves the visual effect.

[First Embodiment]
A visual processing device 1 as a first embodiment of the present invention will be described with reference to FIGS. The visual processing device 1 is a device that performs gradation processing of an image by being incorporated in or connected to a device that handles images, such as a computer, a television, a digital camera, a mobile phone, and a PDA. The visual processing device 1 is characterized in that gradation processing is performed on each of the image areas finely divided as compared with the conventional art.
<Constitution>
FIG. 1 is a block diagram illustrating the structure of the visual processing device 1. The visual processing device 1 includes an image dividing unit 2 that divides an original image input as an input signal IS into a plurality of image regions Pm (1 ≦ m ≦ n: n is the number of divisions of the original image), and each image region Pm. A gradation conversion curve deriving unit 10 for deriving a gradation conversion curve Cm, and a gradation processing unit for loading the gradation conversion curve Cm and outputting an output signal OS obtained by performing gradation processing on each image region Pm. And 5. The gradation conversion curve deriving unit 10 creates a brightness histogram Hm of pixels in the wide-area image region Em composed of the respective image regions Pm and image regions around the image region Pm, and the created brightness. The gradation curve creating unit 4 creates a gradation conversion curve Cm for each image region Pm from the histogram Hm.

<Action>
The operation of each part will be described with reference to FIGS. The image dividing unit 2 divides the original image input as the input signal IS into a plurality (n) of image regions Pm (see FIG. 2). Here, the number of divisions of the original image is larger than the number of divisions (for example, 4 to 16 divisions) of the conventional visual processing device 300 shown in FIG. 33. For example, 4800 is divided into 80 in the horizontal direction and 60 in the vertical direction. Such as division.
The histogram creation unit 3 creates a brightness histogram Hm of the wide-area image region Em for each image region Pm. Here, the wide area image area Em is a set of a plurality of image areas including the respective image areas Pm. For example, 25 image areas having 5 blocks in the vertical direction and 5 blocks in the horizontal direction centering on the image area Pm. Is a set of Depending on the position of the image area Pm, there may be a case where the wide area image area Em of 5 blocks in the vertical direction and 5 blocks in the horizontal direction cannot be taken around the image area Pm. For example, with respect to the image area Pl located around the original image, it is not possible to take a wide area image area El of 5 blocks in the vertical direction and 5 blocks in the horizontal direction around the image area Pl. In this case, an area where the area of 5 blocks in the vertical direction and 5 blocks in the horizontal direction centering on the image area Pl overlaps with the original image is adopted as the wide area image area El. The brightness histogram Hm created by the histogram creation unit 3 indicates the distribution state of the brightness values of all the pixels in the wide area image area Em. That is, in the brightness histograms Hm shown in FIGS. 3A to 3C, the horizontal axis indicates the brightness level of the input signal IS, and the vertical axis indicates the number of pixels.

The gradation curve creating unit 4 accumulates the “number of pixels” of the brightness histogram Hm of the wide area image area Em in the order of brightness, and uses this accumulated curve as the gradation conversion curve Cm of the image area Pm (see FIG. 4). In the gradation conversion curve Cm shown in FIG. 4, the horizontal axis indicates the brightness value of the pixel in the image area Pm in the input signal IS, and the vertical axis indicates the brightness value of the pixel in the image area Pm in the output signal OS. The gradation processing unit 5 loads the gradation conversion curve Cm, and converts the brightness value of the pixel in the image region Pm in the input signal IS based on the gradation conversion curve Cm.
<Visual processing method and visual processing program>
FIG. 5 is a flowchart illustrating a visual processing method in the visual processing device 1. The visual processing method shown in FIG. 5 is realized by hardware in the visual processing device 1 and is a method for performing gradation processing of the input signal IS (see FIG. 1). In the visual processing method shown in FIG. 5, the input signal IS is processed in units of images (steps S10 to S16). The original image input as the input signal IS is divided into a plurality of image regions Pm (1 ≦ m ≦ n: n is the number of divisions of the original image) (step S11), and gradation processing is performed for each image region Pm (step S11). Steps S12 to S15).

A brightness histogram Hm of the pixels of the wide area image area Em composed of the respective image areas Pm and the image areas around the image area Pm is created (step S12). Further, a gradation conversion curve Cm for each image region Pm is created based on the lightness histogram Hm (step S13). Here, the description of the lightness histogram Hm and the gradation conversion curve Cm is omitted (see the section <Action> above). Using the created gradation conversion curve Cm, gradation processing is performed on the pixels in the image region Pm (step S14). Further, it is determined whether or not the processing for all the image regions Pm has been completed (step S15), and the processing of steps S12 to S15 is repeated several times until the processing is determined to be completed. Thus, the processing for each image is completed (step S16).
Note that each step of the visual processing method shown in FIG. 5 may be realized as a visual processing program by a computer or the like.

<effect>
(1)
The gradation conversion curve Cm is created for each image region Pm. Therefore, it is possible to perform appropriate gradation processing as compared with the case where the same gradation conversion is performed on the entire original image.
(2)
The gradation conversion curve Cm created for each image area Pm is created based on the brightness histogram Hm of the wide area image area Em. For this reason, even if the size of each image region Pm is small, sufficient brightness values can be sampled. As a result, an appropriate gradation conversion curve Cm can be created even for a small image region Pm.

(3)
Wide area image areas with respect to adjacent image areas have an overlap. For this reason, the tone conversion curves for adjacent image regions often show similar tendencies. For this reason, it is possible to add a spatial processing effect to the gradation processing for each image region, and it is possible to prevent the boundary between adjacent image regions from being unnaturally conspicuous.
(4)
The size of each image region Pm is smaller than in the past. For this reason, it becomes possible to suppress generation | occurrence | production of the pseudo contour in the image area | region Pm.
<Modification>
The present invention is not limited to the above embodiment, and various modifications can be made without departing from the scope of the invention.

(1)
In the above embodiment, the number of divisions of the original image is 4800 divisions, but the effect of the present invention is not limited to this case, and the same effect can be obtained with other division numbers. is there. Note that the amount of gradation processing and the visual effect are in a trade-off relationship with respect to the number of divisions. That is, when the number of divisions is increased, the amount of gradation processing increases, but a better visual effect (for example, suppression of pseudo contours) can be obtained.
(2)
In the above embodiment, the number of image areas constituting the wide-area image area is 25, but the effect of the present invention is not limited to this case, and the same effect can be obtained with other numbers. It is possible.

[Second Embodiment]
A visual processing device 11 as a second embodiment of the present invention will be described with reference to FIGS. The visual processing device 11 is a device that performs gradation processing of an image by being incorporated in or connected to a device that handles images, such as a computer, a television, a digital camera, a mobile phone, and a PDA. The visual processing device 11 is characterized in that a plurality of gradation conversion curves stored in advance as LUTs are switched and used.
<Constitution>
FIG. 6 is a block diagram illustrating the structure of the visual processing device 11. The visual processing device 11 includes an image dividing unit 12, a selection signal deriving unit 13, and a gradation processing unit 20. The image dividing unit 12 receives the input signal IS and outputs an image area Pm (1 ≦ m ≦ n: n is the number of divisions of the original image) obtained by dividing the original image input as the input signal IS into a plurality of parts. The selection signal deriving unit 13 outputs a selection signal Sm for selecting a gradation conversion curve Cm applied to the gradation processing of each image region Pm. The gradation processing unit 20 includes a gradation processing execution unit 14 and a gradation correction unit 15. The gradation processing execution unit 14 includes a plurality of gradation conversion curve candidates G1 to Gp (p is the number of candidates) as a two-dimensional LUT, and receives an input signal IS and a selection signal Sm as input, and each image region Pm. A gradation processing signal CS obtained by performing gradation processing on the pixels inside is output. The gradation correction unit 15 receives the gradation processing signal CS and outputs an output signal OS obtained by correcting the gradation of the gradation processing signal CS.

(About gradation conversion curve candidates)
The gradation conversion curve candidates G1 to Gp will be described with reference to FIG. The tone conversion curve candidates G1 to Gp are curves that give the relationship between the brightness value of the pixel of the input signal IS and the brightness value of the pixel of the tone processing signal CS. In FIG. 7, the horizontal axis indicates the pixel brightness value in the input signal IS, and the vertical axis indicates the pixel brightness value in the gradation processing signal CS. The gradation conversion curve candidates G1 to Gp are in a monotonically decreasing relationship with respect to the subscripts, and satisfy the relationship of G1 ≧ G2 ≧. For example, the gradation conversion curve candidates G1 to Gp are “power functions” each having the brightness value of the pixel of the input signal IS as a variable, and expressed as Gm = x ^ (δm) (1 ≦ m ≦ p, x is a variable, δm is a constant), and δ1 ≦ δ2 ≦. Here, it is assumed that the lightness value of the input signal IS is in the range of values [0.0 to 1.0].

It should be noted that the relationship between the tone conversion curve candidates G1 to Gp described above is that the input signal IS for the tone conversion curve candidate with a large subscript is small when the input signal IS is small, or for the tone conversion curve candidate with a small subscript. When is large, it may not be established. In such a case, there is almost no effect on the image quality.
The gradation processing execution unit 14 includes gradation conversion curve candidates G1 to Gp as a two-dimensional LUT. That is, the two-dimensional LUT is a look-up table that gives the lightness value of the pixel of the gradation processing signal CS to the lightness value of the pixel of the input signal IS and the selection signal Sm for selecting the gradation conversion curve candidates G1 to Gp. (LUT). FIG. 8 shows an example of this two-dimensional LUT. The two-dimensional LUT 41 shown in FIG. 8 is a matrix of 64 rows and 64 columns, and the respective tone conversion curve candidates G1 to G64 are arranged in the row direction (horizontal direction). In the column direction (vertical direction) of the matrix, for example, the value of the upper 6 bits of the pixel value of the input signal IS represented by 10 bits, that is, the value of the gradation processing signal CS corresponding to the value of the input signal IS divided into 64 stages. Pixel values are lined up. The pixel value of the gradation processing signal CS has a value in the range of [0.0 to 1.0], for example, when the gradation conversion curve candidates G1 to Gp are “power functions”.

<Action>
The operation of each part will be described. The image dividing unit 12 operates in substantially the same manner as the image dividing unit 2 in FIG. 1, and divides the original image input as the input signal IS into a plurality (n) of image regions Pm (see FIG. 2). Here, the number of divisions of the original image is larger than the number of divisions (for example, 4 to 16 divisions) of the conventional visual processing device 300 shown in FIG. 33. For example, 4800 is divided into 80 in the horizontal direction and 60 in the vertical direction. Such as division.
The selection signal deriving unit 13 selects a gradation conversion curve Cm to be applied to each image region Pm from the gradation conversion curve candidates G1 to Gp. Specifically, the selection signal deriving unit 13 calculates the average brightness value of the wide area image area Em of the image area Pm, and selects any one of the gradation conversion curve candidates G1 to Gp according to the calculated average brightness value. I do. That is, the tone conversion curve candidates G1 to Gp are associated with the average brightness value of the wide area image region Em, and the tone conversion curve candidates G1 to Gp with larger subscripts are selected as the average brightness value increases.

Here, the wide area image region Em is the same as that described with reference to FIG. 2 in the first embodiment. That is, the wide area image area Em is a set of a plurality of image areas including each of the image areas Pm. It is. Depending on the position of the image area Pm, there may be a case where the wide area image area Em of 5 blocks in the vertical direction and 5 blocks in the horizontal direction cannot be taken around the image area Pm. For example, with respect to the image area Pl located around the original image, it is not possible to take a wide area image area El of 5 blocks in the vertical direction and 5 blocks in the horizontal direction around the image area Pl. In this case, an area where the area of 5 blocks in the vertical direction and 5 blocks in the horizontal direction centering on the image area Pl overlaps with the original image is adopted as the wide area image area El.
The selection result of the selection signal deriving unit 13 is output as a selection signal Sm indicating any one of the gradation conversion curve candidates G1 to Gp. More specifically, the selection signal Sm is output as the value of the subscripts (1 to p) of the gradation conversion curve candidates G1 to Gp.

The gradation processing execution unit 14 receives the lightness value of the pixel in the image region Pm included in the input signal IS and the selection signal Sm, and uses, for example, the lightness of the gradation processing signal CS using the two-dimensional LUT 41 shown in FIG. Output the value.
The gradation correction unit 15 determines the brightness value of the pixel in the image area Pm included in the gradation processing signal CS, the gradation conversion curve selected for the pixel position, the image area Pm, and the image area around the image area Pm. Correct based on For example, the gradation conversion curve Cm applied to the pixels included in the image region Pm and the gradation conversion curve selected for the image region around the image region Pm are corrected by the internal ratio of the pixel position, and after the correction The brightness value of the pixel is obtained.
The operation of the gradation correction unit 15 will be described in more detail with reference to FIG. FIG. 9 shows gradation conversion curves Co, Cp, Cq, and Cr of image areas Po, Pp, Pq, and Pr (o, p, q, and r are positive integers equal to or less than the division number n (see FIG. 2)). It shows that the key conversion curve candidates Gs, Gt, Gu, and Gv (s, t, u, and v are positive integers less than or equal to the number of gradation conversion curve candidates p) are selected.

Here, the position of the pixel x (value value [x]) of the image area Po to be subjected to gradation correction is set to [i: 1-i] between the center of the image area Po and the center of the image area Pp. Assume that the position is a position where the center of the image area Po and the center of the image area Pq are internally divided into [j: 1-j]. In this case, the brightness value [x ′] of the pixel x after gradation correction is [x ′] = {(1−j) · (1−i) · [Gs] + (1−j) · (i). [Gt] + (j). (1-i). [Gu] + (j). (I). [Gv]}. {[X] / [Gs]}. [Gs], [Gt], [Gu], and [Gv] are the lightness values when the gradation conversion curve candidates Gs, Gt, Gu, and Gv are applied to the lightness value [x]. To do.
<Visual processing method and visual processing program>
FIG. 10 shows a flowchart for explaining the visual processing method in the visual processing device 11. The visual processing method shown in FIG. 10 is realized by hardware in the visual processing device 11, and is a method for performing gradation processing of the input signal IS (see FIG. 6). In the visual processing method shown in FIG. 10, the input signal IS is processed in units of images (steps S20 to S26). The original image input as the input signal IS is divided into a plurality of image regions Pm (1 ≦ m ≦ n: n is the number of divisions of the original image) (step S21), and gradation processing is performed for each image region Pm (step S21). Steps S22 to S24).

In the processing for each image region Pm, the gradation conversion curve Cm applied to each image region Pm is selected from the gradation conversion curve candidates G1 to Gp (step S22). Specifically, the average brightness value of the wide area image area Em of the image area Pm is calculated, and any one of the gradation conversion curve candidates G1 to Gp is selected according to the calculated average brightness value. The tone conversion curve candidates G1 to Gp are associated with the average brightness value of the wide area image region Em, and the tone conversion curve candidates G1 to Gp with larger subscripts are selected as the average brightness value increases. Here, the description of the wide area image region Em is omitted (see the column of <Action> above).
For example, FIG. 8 shows the brightness value of the pixel in the image area Pm included in the input signal IS and the selection signal Sm indicating the gradation conversion curve candidate selected in step S22 among the gradation conversion curve candidates G1 to Gp. The brightness value of the gradation processing signal CS is output using the two-dimensional LUT 41 shown (step S23). Further, it is determined whether or not the processing for all the image regions Pm has been completed (step S24), and the processing of steps S22 to S24 is repeated several times until the processing is determined to be completed. Thus, the processing for each image area is completed.

The brightness value of the pixel in the image area Pm included in the gradation processing signal CS is corrected based on the position of the pixel and the gradation conversion curve selected for the image area Pm and the image area around the image area Pm. (Step S25). For example, the gradation conversion curve Cm applied to the pixels included in the image region Pm and the gradation conversion curve selected for the image region around the image region Pm are corrected by the internal ratio of the pixel position, and after the correction Are obtained. The detailed description of the correction will be omitted (see the section <Action> in FIG. 9).
Thus, the processing for each image is completed (step S26).
Each step of the visual processing method shown in FIG. 10 may be realized as a visual processing program by a computer or the like.
<effect>
According to the present invention, it is possible to obtain substantially the same effect as the <Effect> of the above [First Embodiment]. Hereinafter, effects unique to the second embodiment will be described.

(1)
The gradation conversion curve Cm selected for each image area Pm is created based on the average brightness value of the wide area image area Em. For this reason, even if the size of the image region Pm is small, it is possible to sample a sufficient brightness value. As a result, an appropriate gradation conversion curve Cm can be selected and applied to a small image region Pm.
(2)
The gradation processing execution unit 14 has a two-dimensional LUT created in advance. For this reason, it is possible to reduce the processing load required for gradation processing, more specifically, the processing load required for creating the gradation conversion curve Cm. As a result, it is possible to speed up the processing required for the gradation processing of the image region Pm.

(3)
The gradation processing execution unit 14 executes gradation processing using a two-dimensional LUT. The two-dimensional LUT is read from a storage device such as a hard disk or a ROM provided in the visual processing device 11 and used for gradation processing. By changing the contents of the two-dimensional LUT to be read out, various gradation processes can be realized without changing the hardware configuration. That is, it is possible to realize gradation processing more suitable for the characteristics of the original image.
(4)
The gradation correction unit 15 corrects the gradation of the pixels in the image region Pm that has been subjected to gradation processing using one gradation conversion curve Cm. For this reason, it is possible to obtain an output signal OS subjected to more appropriate gradation processing. For example, it becomes possible to suppress the generation of pseudo contours. Further, in the output signal OS, it is possible to further prevent the joint at the boundary of each image region Pm from being unnaturally conspicuous.

<Modification>
The present invention is not limited to the above embodiment, and various modifications can be made without departing from the scope of the invention.
(1)
In the above embodiment, the number of divisions of the original image is 4800 divisions, but the effect of the present invention is not limited to this case, and the same effect can be obtained with other division numbers. is there. Note that the amount of gradation processing and the visual effect are in a trade-off relationship with respect to the number of divisions. That is, when the number of divisions is increased, the processing amount of gradation processing increases, but a better visual effect (for example, an image in which pseudo contour is suppressed) can be obtained.
(2)
In the above embodiment, the number of image areas constituting the wide-area image area is 25, but the effect of the present invention is not limited to this case, and the same effect can be obtained with other numbers. It is possible.

(3)
In the above-described embodiment, the two-dimensional LUT 41 including a 64 × 64 matrix is taken as an example of the two-dimensional LUT. Here, the effect of the present invention is not limited to the two-dimensional LUT of this size. For example, it may be a matrix in which more gradation conversion curve candidates are arranged in the row direction. Further, the pixel values of the gradation processing signal CS corresponding to the values obtained by dividing the pixel values of the input signal IS into finer steps may be arranged in the column direction of the matrix. Specifically, for example, the pixel value of the gradation processing signal CS may be arranged for each pixel value of the input signal IS represented by 10 bits.
If the size of the two-dimensional LUT is increased, more appropriate gradation processing can be performed, and if the size is decreased, the memory for storing the two-dimensional LUT can be reduced.

(4)
In the above embodiment, in the column direction of the matrix, for example, the gradation processing signal CS corresponding to the value of the upper 6 bits of the pixel value of the input signal IS represented by 10 bits, that is, the value of the input signal IS divided into 64 stages. It was explained that the pixel values of are arranged. Here, the gradation processing signal CS may be output as a matrix component that is linearly interpolated by the gradation processing execution unit 14 with the lower 4 bits of the pixel value of the input signal IS. That is, in the column direction of the matrix, for example, the components of the matrix corresponding to the upper 6 bits of the pixel value of the input signal IS represented by 10 bits are arranged, and the upper 6 bits of the pixel value of the input signal IS are arranged. The matrix component and the matrix component (for example, the component one row lower in FIG. 8) with respect to the value obtained by adding [1] to the upper 6 bits of the pixel value of the input signal IS are the pixel values of the input signal IS. Is linearly interpolated using the value of the lower 4 bits and output as a gradation processing signal CS.

As a result, even if the size of the two-dimensional LUT 41 (see FIG. 8) is small, more appropriate gradation processing can be performed.
(5)
In the above embodiment, it has been described that the gradation conversion curve Cm to be applied to the image area Pm is selected based on the average brightness value of the wide area image area Em. Here, the method of selecting the gradation conversion curve Cm is not limited to this method. For example, the gradation conversion curve Cm to be applied to the image area Pm may be selected based on the maximum brightness value or the minimum brightness value of the wide area image area Em. In selecting the gradation conversion curve Cm, the value [Sm] of the selection signal Sm may be the average brightness value, the maximum brightness value, or the minimum brightness value of the wide area image area Em. In this case, the gradation conversion curve candidates G1 to G64 are associated with the respective values obtained by dividing the possible values of the selection signal Sm into 64 levels.

For example, the gradation conversion curve Cm applied to the image region Pm may be selected as follows. That is, an average brightness value is obtained for each image region Pm, and a provisional selection signal Sm ′ for each image region Pm is obtained from each average brightness value. Here, the provisional selection signal Sm ′ has the values of the subscript numbers of the gradation conversion curve candidates G1 to Gp as values. Further, for each image area included in the wide area image area Em, the value of the temporary selection signal Sm ′ is averaged to obtain the value [Sm] of the selection signal Sm of the image area Pm, and the gradation conversion curve candidates G1 to Gp Among these, a candidate having an integer closest to the value [Sm] as a subscript is selected as the gradation conversion curve Cm.
(6)
In the above embodiment, it has been described that the gradation conversion curve Cm to be applied to the image area Pm is selected based on the average brightness value of the wide area image area Em. Here, the gradation conversion curve Cm to be applied to the image region Pm may be selected based on a weighted average (weighted average) instead of a simple average of the wide area image region Em. For example, as shown in FIG. 11, the average brightness value of each image area constituting the wide area image area Em is obtained, and the image areas Ps1, Ps2,. For ・, the average brightness value of the wide-area image region Em is obtained by reducing or excluding weights.

As a result, even when the wide area image region Em includes an area specific to brightness (for example, when the wide area image area Em includes a boundary between two objects having different brightness values), the image area Pm is applied. Therefore, the influence of the brightness value of the specific area on the selection of the gradation conversion curve Cm is reduced, and more appropriate gradation processing is performed.
(7)
In the embodiment, the presence of the gradation correction unit 15 may be arbitrary. That is, even when the gradation processing signal CS is output, as compared with the conventional visual processing device 300 (see FIG. 33), it is the same as described in <Effect> of the [first embodiment]. Effects and [Effects] of [Second Embodiment] (1) It is possible to obtain the same effects as described in (2).
(8)
In the above embodiment, the gradation conversion curve candidates G1 to Gp are in a monotonically decreasing relationship with respect to the subscript, and the relationship of G1 ≧ G2 ≧. Explained that Here, the tone conversion curve candidates G1 to Gp included in the two-dimensional LUT may not satisfy the relationship of G1 ≧ G2 ≧... ≧ Gp with respect to a part of the brightness value of the pixel of the input signal IS. Good. That is, any one of the gradation conversion curve candidates G1 to Gp may be in a crossing relationship with each other.

For example, if the value of the input signal IS is large but the average brightness value of the wide area image area Em is small, such as a small light part in a dark night scene (neon part in a night scene, etc.), gradation processing is performed. The influence of the image signal value on the image quality is small. In such a case, the gradation conversion curve candidates G1 to Gp included in the two-dimensional LUT satisfy the relationship of G1 ≧ G2 ≧... Gp with respect to a part of the brightness value of the pixel of the input signal IS. It does not have to be. That is, the value stored in the two-dimensional LUT may be arbitrary in a part where the value after gradation processing has little influence on the image quality.
Even when the values stored in the two-dimensional LUT are arbitrary, the values stored for the input signal IS and the selection signal Sm having the same value are the same as the values of the input signal IS and the selection signal Sm. It is desirable to maintain a monotonically increasing or monotonically decreasing relationship.

In the above embodiment, the gradation conversion curve candidates G1 to Gp included in the two-dimensional LUT are described as “power functions”. Here, the gradation conversion curve candidates G1 to Gp may not be strictly formulated as “power functions”. Further, it may be a function having a shape such as an S-shape or an inverted S-shape.
(9)
The visual processing device 11 may further include a profile data creation unit that creates profile data that is a value stored in the two-dimensional LUT. Specifically, the profile data creation unit includes an image dividing unit 2 and a tone conversion curve deriving unit 10 in the visual processing device 1 (see FIG. 1). The set is stored in the two-dimensional LUT as profile data.

Further, each of the gradation conversion curves stored in the two-dimensional LUT may be associated with the spatially processed input signal IS. In this case, in the visual processing device 11, the image dividing unit 12 and the selection signal deriving unit 13 may be replaced with a spatial processing unit that spatially processes the input signal IS.
(10)
In the above embodiment, the brightness value of the pixel of the input signal IS may not be a value in the range of the value [0.0 to 1.0]. When the input signal IS is input as a value in another range, the value in that range may be normalized to a value [0.0 to 1.0]. Further, normalization is not performed, and the values handled in the above-described processing may be changed as appropriate.
(11)
Each of the gradation conversion curve candidates G1 to Gp is a gradation conversion curve that performs gradation processing on an input signal IS having a dynamic range wider than the normal dynamic range and outputs a gradation processing signal CS having a normal dynamic range. There may be.

In recent years, by using a CCD with good S / N with a reduced amount of light, opening the electronic shutter twice long or short, or using a sensor with low-sensitivity / high-sensitivity pixels, it is possible to achieve a higher dynamic range than the normal dynamic range. Development of devices that can handle a dynamic range that is one to three digits wider is advancing.
Accordingly, even when the input signal IS has a wider dynamic range than a normal dynamic range (for example, a signal in the range of value [0.0 to 1.0]), gradation processing can be appropriately performed. It has been demanded.
Here, as shown in FIG. 12, the gradation processing signal CS having the value [0.0 to 1.0] is output even for the input signal IS in the range exceeding the value [0.0 to 1.0]. Such a gradation conversion curve is used.

As a result, it is possible to perform appropriate gradation processing even on an input signal IS having a wide dynamic range, and to output a gradation processing signal CS having a normal dynamic range.
In the above-described embodiment, “the pixel value of the gradation processing signal CS is, for example, in the range of values [0.0 to 1.0] when the gradation conversion curve candidates G1 to Gp are“ power functions ”. Has a value. ". Here, the pixel value of the gradation processing signal CS is not limited to this range. For example, the gradation conversion curve candidates G1 to Gp may perform dynamic range compression on the input signal IS having a value [0.0 to 1.0].
(12)
In the embodiment described above, “the gradation processing execution unit 14 has the gradation conversion curve candidates G1 to Gp as a two-dimensional LUT”. Here, the gradation processing execution unit 14 may have a one-dimensional LUT that stores the relationship between the curve parameter for specifying the gradation conversion curve candidates G1 to Gp and the selection signal Sm.

"Constitution"
FIG. 13 is a block diagram illustrating the structure of a gradation processing execution unit 44 as a modification of the gradation processing execution unit 14. The gradation processing execution unit 44 receives the input signal IS and the selection signal Sm, and outputs a gradation processing signal CS that is the input signal IS subjected to gradation processing. The gradation processing execution unit 44 includes a curve parameter output unit 45 and a calculation unit 48.
The curve parameter output unit 45 includes a first LUT 46 and a second LUT 47. The first LUT 46 and the second LUT 47 receive the selection signal Sm and output the curve parameters P1 and P2 of the gradation conversion curve candidate Gm specified by the selection signal Sm, respectively.
The calculation unit 48 receives the curve parameters P1 and P2 and the input signal IS and outputs the gradation processing signal CS.

<< About 1D LUT >>
The first LUT 46 and the second LUT 47 are one-dimensional LUTs that store the values of the curve parameters P1 and P2 for the selection signal Sm, respectively. Before describing the first LUT 46 and the second LUT 47 in detail, the contents of the curve parameters P1 and P2 will be described.
The relationship between the curve parameters P1 and P2 and the gradation conversion curve candidates G1 to Gp will be described with reference to FIG. FIG. 14 shows tone conversion curve candidates G1 to Gp. Here, the gradation conversion curve candidates G1 to Gp are in a monotonically decreasing relationship with respect to the subscript, and satisfy the relationship of G1 ≧ G2 ≧... ≧ Gp with respect to the brightness values of the pixels of all the input signals IS. ing. It should be noted that the relationship between the tone conversion curve candidates G1 to Gp described above is that the input signal IS for the tone conversion curve candidate with a large subscript is small when the input signal IS is small, or for the tone conversion curve candidate with a small subscript. This may not be the case when the is large.

The curve parameters P1 and P2 are output as the value of the gradation processing signal CS with respect to a predetermined value of the input signal IS. That is, when the gradation conversion curve candidate Gm is designated by the selection signal Sm, the value of the curve parameter P1 is output as the value [R1m] of the gradation conversion curve candidate Gm with respect to the predetermined value [X1] of the input signal IS. The value of the curve parameter P2 is output as the value [R2m] of the gradation conversion curve candidate Gm for the predetermined value [X2] of the input signal IS. Here, the value [X2] is larger than the value [X1].
Next, the first LUT 46 and the second LUT 47 will be described.
The first LUT 46 and the second LUT 47 store the values of the curve parameters P1 and P2 for the selection signal Sm, respectively. More specifically, for example, for each selection signal Sm given as a 6-bit signal, the values of the curve parameters P1 and P2 are given in 6 bits. Here, the number of bits secured for the selection signal Sm and the curve parameters P1 and P2 is not limited to this.

The relationship between the curve parameters P1 and P2 and the selection signal Sm will be described with reference to FIG. FIG. 15 shows changes in the values of the curve parameters P1 and P2 with respect to the selection signal Sm. The first LUT 46 and the second LUT 47 store the values of the curve parameters P1 and P2 for the respective selection signals Sm. For example, the value [R1m] is stored as the value of the curve parameter P1 for the selection signal Sm, and the value [R2m] is stored as the value of the curve parameter P2.
By the first LUT 46 and the second LUT 47 described above, the curve parameters P1 and P2 are output for the input selection signal Sm.
<< Calculation unit 48 >>
The computing unit 48 derives the gradation processing signal CS for the input signal IS based on the acquired curve parameters P1 and P2 (value [R1m] and value [R2m]). The specific procedure is described below. Here, the value of the input signal IS is given in the range of values [0.0 to 1.0]. Further, the gradation conversion curve candidates G1 to Gp convert the input signal IS given in the range of the value [0.0 to 1.0] into the range of the value [0.0 to 1.0]. And The present invention can also be applied when the input signal IS is not limited to this range.

First, the calculation unit 48 compares the value of the input signal IS with predetermined values [X1] and [X2].
When the value of the input signal IS (value [X]) is not less than [0.0] and less than [X1], on the straight line connecting the origin and the coordinates ([X1], [R1m]) in FIG. A value of gradation processing signal CS (value [Y]) with respect to value [X] is obtained. More specifically, the value [Y] is obtained by the following formula [Y] = ([X] / [X1]) * [R1m].
When the value of the input signal IS is not less than [X1] and less than [X2], the value on the straight line connecting the coordinates ([X1], [R1m]) and the coordinates ([X2], [R2m]) in FIG. A value [Y] for [X] is determined. More specifically, the value [Y] is expressed by the following formula [Y] = [R1m] + {([R2m] − [R1m]) / ([X2] − [X1])} * ([X] − [ X1]).

When the value of the input signal IS is not less than [X2] and not more than [1.0], the coordinates ([X2], [R2m]) and the coordinates ([1.0], [1.0]) in FIG. A value [Y] with respect to the value [X] is obtained on the connecting straight line. More specifically, the value [Y] is expressed by the following formula [Y] = [R2m] + {([1.0] − [R2m]) / ([1.0] − [X2])} * ([ X]-[X2]).
Through the above calculation, the calculation unit 48 derives the gradation processing signal CS for the input signal IS.
<< Tone Processing Method / Program >>
The above processing may be executed by a computer or the like as a gradation processing program. The gradation processing program is a program for causing a computer to execute the gradation processing method described below.

The gradation processing method is a method of acquiring the input signal IS and the selection signal Sm and outputting the gradation processing signal CS, and is characterized in that the input signal IS is subjected to gradation processing using a one-dimensional LUT. is doing.
First, when the selection signal Sm is acquired, the curve parameters P1 and P2 are output from the first LUT 46 and the second LUT 47. Detailed descriptions of the first LUT 46, the second LUT 47, and the curve parameters P1 and P2 are omitted.
Further, gradation processing of the input signal IS is performed based on the curve parameters P1 and P2. The detailed content of the gradation processing is omitted because it has been described in the description of the calculation unit 48.
With the above gradation processing method, the gradation processing signal CS for the input signal IS is derived.

"effect"
A gradation processing execution unit 44 as a modification of the gradation processing execution unit 14 includes two one-dimensional LUTs instead of a two-dimensional LUT. For this reason, it is possible to reduce the storage capacity for storing the lookup table.
<Modification>
(1)
In the above modification, it has been described that “the values of the curve parameters P1 and P2 are the values of the tone conversion curve candidate Gm with respect to the predetermined value of the input signal IS”. Here, the curve parameters P1 and P2 may be other curve parameters of the tone conversion curve candidate Gm. A specific description will be added below.

(1-1)
The curve parameter may be the slope of the gradation conversion curve candidate Gm. This will be specifically described with reference to FIG. When the gradation conversion curve candidate Gm is designated by the selection signal Sm, the value of the curve parameter P1 is the slope value [K1m] of the gradation conversion curve candidate Gm in the predetermined range [0.0 to X1] of the input signal IS. The value of the curve parameter P2 is the slope value [K2m] of the gradation conversion curve candidate Gm in the predetermined range [X1 to X2] of the input signal IS.
The relationship between the curve parameters P1 and P2 and the selection signal Sm will be described with reference to FIG. FIG. 16 shows changes in the values of the curve parameters P1 and P2 with respect to the selection signal Sm. The first LUT 46 and the second LUT 47 store the values of the curve parameters P1 and P2 for the respective selection signals Sm. For example, the value [K1m] is stored as the value of the curve parameter P1 for the selection signal Sm, and the value [K2m] is stored as the value of the curve parameter P2.

By the first LUT 46 and the second LUT 47 described above, the curve parameters P1 and P2 are output for the input selection signal Sm.
The computing unit 48 derives a gradation processing signal CS for the input signal IS based on the acquired curve parameters P1 and P2. The specific procedure is described below.
First, the calculation unit 48 compares the value of the input signal IS with predetermined values [X1] and [X2].
When the value of the input signal IS (value [X]) is not less than [0.0] and less than [X1], the origin and coordinates ([X1], [K1m] * [X1] in FIG. Y1])))), the value of the gradation processing signal CS for the value [X] (referred to as value [Y]) is obtained. More specifically, the value [Y] is obtained by the following equation [Y] = [K1m] * [X].

When the value of the input signal IS is [X1] or more and less than [X2], the coordinates ([X1], [Y1]) and the coordinates ([X2], [K1m] * [X1] + [K2m] * in FIG. 14) A value [Y] with respect to the value [X] is obtained on a straight line connecting ([X2]-[X1]) (hereinafter referred to as [Y2]). More specifically, the value [Y] is obtained by the following formula [Y] = [Y1] + [K2m] * ([X] − [X1]).
When the value of the input signal IS is [X2] or more and [1.0] or less, on the straight line connecting the coordinates ([X2], [Y2]) and the coordinates (1.0, 1.0) in FIG. The value [Y] for the value [X] is obtained. More specifically, the value [Y] is expressed by the following formula [Y] = [Y2] + {([1.0] − [Y2]) / ([1.0] − [X2])} * ([ X]-[X2]).

Through the above calculation, the calculation unit 48 derives the gradation processing signal CS for the input signal IS.
(1-2)
The curve parameter may be a coordinate on the gradation conversion curve candidate Gm. This will be specifically described with reference to FIG. When the gradation conversion curve candidate Gm is specified by the selection signal Sm, the value of the curve parameter P1 is the value [Mm] of one component of the coordinates on the gradation conversion curve candidate Gm, and the value of the curve parameter P2 is The value [Nm] of the other component of the coordinates on the gradation conversion curve candidate Gm. Further, the gradation conversion curve candidates G1 to Gp are all curves that pass through the coordinates (X1, Y1).
The relationship between the curve parameters P1 and P2 and the selection signal Sm will be described with reference to FIG. FIG. 18 shows changes in the values of the curve parameters P1 and P2 with respect to the selection signal Sm. The first LUT 46 and the second LUT 47 store the values of the curve parameters P1 and P2 for the respective selection signals Sm. For example, the value [Mm] is stored as the value of the curve parameter P1 for the selection signal Sm, and the value [Nm] is stored as the value of the curve parameter P2.

By the first LUT 46 and the second LUT 47 described above, the curve parameters P1 and P2 are output for the input selection signal Sm.
In the calculation unit 48, the gradation processing signal CS is derived from the input signal IS by the same processing as that of the modification described with reference to FIG. Detailed description is omitted.
(1-3)
The above modification is an example, and the curve parameters P1 and P2 may be other curve parameters of the tone conversion curve candidate Gm.
Further, the number of curve parameters is not limited to the above. There may be fewer or more.
In the description of the calculation unit 48, the calculation for the case where the gradation conversion curve candidates G1 to Gp are curves composed of straight line segments is described. Here, when the coordinates on the gradation conversion curve candidates G1 to Gp are given as curve parameters, a smooth curve passing through the given coordinates is created (curve fitting), and the created curve is used. A gradation conversion process may be performed.

(2)
In the above modification, “the curve parameter output unit 45 includes the first LUT 46 and the second LUT 47” has been described. Here, the curve parameter output unit 45 may not include an LUT that stores the values of the curve parameters P1 and P2 with respect to the value of the selection signal Sm.
In this case, the curve parameter output unit 45 calculates the values of the curve parameters P1 and P2. More specifically, the curve parameter output unit 45 stores parameters representing graphs of the curve parameters P1 and P2 shown in FIG. 15, FIG. 16, FIG. The curve parameter output unit 45 specifies graphs of the curve parameters P1 and P2 from the stored parameters. Further, the values of the curve parameters P1 and P2 with respect to the selection signal Sm are output using the graphs of the curve parameters P1 and P2.

Here, the parameters for specifying the graphs of the curve parameters P1 and P2 are coordinates on the graph, inclination of the graph, curvature, and the like. For example, the curve parameter output unit 45 stores the coordinates of two points on the graph of the curve parameters P1 and P2 shown in FIG. 15, and the straight line connecting the coordinates of the two points is represented by the graph of the curve parameters P1 and P2. Used as
Here, when specifying the graphs of the curve parameters P1 and P2 from the parameters, not only linear approximation but also broken line approximation, curve approximation, or the like may be used.
This makes it possible to output curve parameters without using a memory for storing the LUT. That is, it is possible to further reduce the capacity of the memory provided in the apparatus.

[Third Embodiment]
A visual processing device 21 as a third embodiment of the present invention will be described with reference to FIGS. The visual processing device 21 is a device that performs gradation processing of an image by being incorporated in or connected to a device that handles images, such as a computer, a television, a digital camera, a mobile phone, and a PDA. The visual processing device 21 is characterized in that a plurality of gradation conversion curves stored in advance as LUTs are switched for each pixel to be subjected to gradation processing.
<Constitution>
FIG. 19 is a block diagram illustrating the structure of the visual processing device 21. The visual processing device 21 includes an image dividing unit 22, a selection signal deriving unit 23, and a gradation processing unit 30. The image dividing unit 22 receives the input signal IS and outputs an image area Pm (1 ≦ m ≦ n: n is the number of divisions of the original image) obtained by dividing the original image input as the input signal IS into a plurality of parts. The selection signal deriving unit 23 outputs a selection signal Sm for selecting the gradation conversion curve Cm for each image region Pm. The gradation processing unit 30 includes a selection signal correction unit 24 and a gradation processing execution unit 25. The selection signal correction unit 24 receives the selection signal Sm and outputs a selection signal SS for each pixel, which is a signal obtained by correcting the selection signal Sm for each image region Pm. The gradation processing execution unit 25 includes a plurality of gradation conversion curve candidates G1 to Gp (p is the number of candidates) as a two-dimensional LUT, and receives an input signal IS and a selection signal SS for each pixel as input. An output signal OS obtained by performing gradation processing on the pixel is set as an output.

(About gradation conversion curve candidates)
The gradation conversion curve candidates G1 to Gp are substantially the same as those described with reference to FIG. 7 in [Second Embodiment], and thus description thereof is omitted here. However, in the present embodiment, the tone conversion curve candidates G1 to Gp are curves that give the relationship between the brightness value of the pixel of the input signal IS and the brightness value of the pixel of the output signal OS.
The gradation processing execution unit 25 includes gradation conversion curve candidates G1 to Gp as a two-dimensional LUT. That is, the two-dimensional LUT is a look-up table (LUT) that gives the lightness value of the pixel of the output signal OS to the lightness value of the pixel of the input signal IS and the selection signal SS for selecting the gradation conversion curve candidates G1 to Gp. ). A specific example is substantially the same as that described with reference to FIG. 8 in [Second Embodiment], and thus the description thereof is omitted here. However, in the present embodiment, the pixel values of the output signal OS are arranged in the column direction of the matrix with respect to the upper 6 bits of the pixel value of the input signal IS represented by 10 bits, for example.

<Action>
The operation of each part will be described. The image dividing unit 22 operates in substantially the same manner as the image dividing unit 2 in FIG. 1, and divides the original image input as the input signal IS into a plurality (n) of image regions Pm (see FIG. 2). Here, the number of divisions of the original image is larger than the number of divisions (for example, 4 to 16 divisions) of the conventional visual processing device 300 shown in FIG. 33. For example, 4800 is divided into 80 in the horizontal direction and 60 in the vertical direction. Such as division.
The selection signal deriving unit 23 selects a gradation conversion curve Cm from the gradation conversion curve candidates G1 to Gp for each image region Pm. Specifically, the selection signal deriving unit 23 calculates the average brightness value of the wide area image area Em of the image area Pm, and selects any one of the gradation conversion curve candidates G1 to Gp according to the calculated average brightness value. I do. That is, the tone conversion curve candidates G1 to Gp are associated with the average brightness value of the wide area image region Em, and the tone conversion curve candidates G1 to Gp with larger subscripts are selected as the average brightness value increases.

Here, the wide area image region Em is the same as that described with reference to FIG. 2 in the first embodiment. That is, the wide area image area Em is a set of a plurality of image areas including each of the image areas Pm. It is. Depending on the position of the image area Pm, there may be a case where the wide area image area Em of 5 blocks in the vertical direction and 5 blocks in the horizontal direction cannot be taken around the image area Pm. For example, with respect to the image area Pl located around the original image, it is not possible to take a wide area image area El of 5 blocks in the vertical direction and 5 blocks in the horizontal direction around the image area Pl. In this case, an area where the area of 5 blocks in the vertical direction and 5 blocks in the horizontal direction centering on the image area Pl overlaps with the original image is adopted as the wide area image area El.
The selection result of the selection signal deriving unit 23 is output as a selection signal Sm indicating any one of the gradation conversion curve candidates G1 to Gp. More specifically, the selection signal Sm is output as the value of the subscripts (1 to p) of the gradation conversion curve candidates G1 to Gp.

The selection signal correction unit 24 performs pixel-by-pixel selection for selecting a gradation conversion curve for each pixel constituting the input signal IS by correction using each selection signal Sm output for each image region Pm. The selection signal SS is output. For example, the selection signal SS for the pixels included in the image region Pm is obtained by correcting the value of the selection signal output for the image region Pm and the image region around the image region Pm with the internal division ratio of the pixel position. .
The operation of the selection signal correction unit 24 will be described in more detail with reference to FIG. In FIG. 20, selection signals So, Sp, Sq, and Sr are output for image regions Po, Pp, Pq, and Pr (o, p, q, and r are positive integers equal to or less than the division number n (see FIG. 2)). It shows the state that was done.
Here, the position of the pixel x to be subjected to gradation correction is divided into [i: 1-i] between the center of the image area Po and the center of the image area Pp, and the center of the image area Po and the image. It is assumed that the position is a position that internally divides the center of the region Pq into [j: 1-j]. In this case, the value [SS] of the selection signal SS for the pixel x is [SS] = {(1-j). (1-i). [So] + (1-j). (I). [Sp] + (J). (1-i). [Sq] + (j). (I). [Sr]}. [So], [Sp], [Sq], and [Sr] are values of the selection signals So, Sp, Sq, and Sr.

The gradation processing execution unit 25 receives the lightness value of the pixel included in the input signal IS and the selection signal SS, and outputs the lightness value of the output signal OS using, for example, a two-dimensional LUT 41 shown in FIG.
When the value [SS] of the selection signal SS is not equal to the subscripts (1 to p) of the gradation conversion curve candidates G1 to Gp included in the two-dimensional LUT 41, an integer closest to the value [SS] is added. The tone conversion curve candidates G1 to Gp to be used as characters are used for tone processing of the input signal IS.
<Visual processing method and visual processing program>
FIG. 21 shows a flowchart for explaining a visual processing method in the visual processing device 21. The visual processing method shown in FIG. 21 is realized by hardware in the visual processing device 21, and is a method for performing gradation processing of the input signal IS (see FIG. 19). In the visual processing method shown in FIG. 21, the input signal IS is processed in units of images (steps S30 to S37). The original image input as the input signal IS is divided into a plurality of image regions Pm (1 ≦ m ≦ n: n is the number of divisions of the original image) (step S31), and a gradation conversion curve Cm is generated for each image region Pm. A gradation conversion curve is selected for each pixel of the original image on the basis of the selection signal Sm for selecting the gradation conversion curve Cm for each image region Pm (steps S32 to S33). Tone processing is performed (steps S34 to S36).

Specific explanation will be given for each step.
A gradation conversion curve Cm is selected from the gradation conversion curve candidates G1 to Gp for each image region Pm (step S32). Specifically, the average brightness value of the wide area image area Em of the image area Pm is calculated, and any one of the gradation conversion curve candidates G1 to Gp is selected according to the calculated average brightness value. The tone conversion curve candidates G1 to Gp are associated with the average brightness value of the wide area image region Em, and the tone conversion curve candidates G1 to Gp with larger subscripts are selected as the average brightness value increases. Here, the description of the wide area image region Em is omitted (see the column of <Action> above). The selection result is output as a selection signal Sm indicating any one of the gradation conversion curve candidates G1 to Gp. More specifically, the selection signal Sm is output as the value of the subscripts (1 to p) of the gradation conversion curve candidates G1 to Gp. Further, it is determined whether or not the processing for all the image areas Pm has been completed (step S33), and the processing in steps S32 to S33 is repeated several times until the processing is determined to be completed. Thus, the processing for each image area is completed.

By using the selection signal Sm output for each image region Pm, a selection signal SS for each pixel for selecting a gradation conversion curve is output for each pixel constituting the input signal IS. (Step S34). For example, the selection signal SS for the pixels included in the image region Pm is obtained by correcting the value of the selection signal output for the image region Pm and the image region around the image region Pm with the internal division ratio of the pixel position. . The detailed description of the correction will be omitted (see the section <Action> in FIG. 20).
The brightness value of the pixel included in the input signal IS and the selection signal SS are input, and the brightness value of the output signal OS is output using, for example, the two-dimensional LUT 41 shown in FIG. 8 (step S35). Further, it is determined whether or not the processing for all the pixels has been completed (step S36), and the processing of steps S34 to S36 is repeated several times until it is determined that the processing has been completed. Thus, the process for each image is completed.

Each step of the visual processing method shown in FIG. 21 may be realized as a visual processing program by a computer or the like.
<effect>
According to the present invention, it is possible to obtain substantially the same effect as the <Effect> of the above [First Embodiment] and [Second Embodiment]. Hereinafter, effects unique to the third embodiment will be described.
(1)
The gradation conversion curve Cm selected for each image area Pm is created based on the average brightness value of the wide area image area Em. For this reason, even if the size of the image region Pm is small, it is possible to sample a sufficient brightness value. As a result, an appropriate gradation conversion curve Cm is selected even for a small image region Pm.

(2)
The selection signal correction unit 24 outputs a selection signal SS for each pixel by correction based on the selection signal Sm output in units of image regions. The pixels of the original image constituting the input signal IS are subjected to gradation processing using the gradation conversion curve candidates G1 to Gp designated by the selection signal SS for each pixel. For this reason, it is possible to obtain an output signal OS subjected to more appropriate gradation processing. For example, it becomes possible to suppress the generation of pseudo contours. Further, in the output signal OS, it is possible to further prevent the joint at the boundary of each image region Pm from being unnaturally conspicuous.
(3)
The gradation processing execution unit 25 has a two-dimensional LUT created in advance. For this reason, it is possible to reduce the processing load required for the gradation processing, more specifically, it is possible to reduce the processing load required for creating the gradation conversion curve Cm. As a result, the gradation processing can be speeded up.

(4)
The gradation processing execution unit 25 executes gradation processing using a two-dimensional LUT. Here, the contents of the two-dimensional LUT are read from a storage device such as a hard disk or a ROM provided in the visual processing device 21 and used for gradation processing. By changing the contents of the two-dimensional LUT to be read out, various gradation processes can be realized without changing the hardware configuration. That is, it is possible to realize gradation processing more suitable for the characteristics of the original image.
<Modification>
The present invention is not limited to the above embodiment, and various modifications can be made without departing from the scope of the invention. For example, it is possible to apply substantially the same modification as the above [Second Embodiment] <Modification> to the third embodiment. In particular, in (10) to (12) of [Second Embodiment] <Modification>, the selection signal Sm is replaced with the selection signal SS, and the gradation processing signal CS is replaced with the output signal OS. is there.

Hereinafter, modifications specific to the third embodiment will be described.
(1)
In the above-described embodiment, the two-dimensional LUT 41 including a 64 × 64 matrix is taken as an example of the two-dimensional LUT. Here, the effect of the present invention is not limited to the two-dimensional LUT of this size. For example, it may be a matrix in which more gradation conversion curve candidates are arranged in the row direction. Further, the pixel values of the output signal OS corresponding to the values obtained by dividing the pixel values of the input signal IS into smaller steps may be arranged in the column direction of the matrix. Specifically, for example, the pixel value of the output signal OS may be arranged for each pixel value of the input signal IS represented by 10 bits.
If the size of the two-dimensional LUT is increased, more appropriate gradation processing can be performed, and if the size is decreased, the memory for storing the two-dimensional LUT can be reduced.

(2)
In the above embodiment, when the value [SS] of the selection signal SS is not equal to the subscripts (1 to p) of the gradation conversion curve candidates G1 to Gp included in the two-dimensional LUT 41 (see FIG. 8), the value [ It has been described that the gradation conversion curve candidates G1 to Gp with the integer closest to SS] as subscripts are used for the gradation processing of the input signal IS. Here, when the value [SS] of the selection signal SS is not equal to the subscripts (1 to p) of the gradation conversion curve candidates G1 to Gp included in the two-dimensional LUT 41, the value [SS] of the selection signal SS is set. Gradation conversion curve candidate Gk (1 ≦ k ≦ p−1) with a maximum integer (k) not exceeding as a subscript and gradation conversion curve with a minimum integer (k + 1) exceeding [SS] as a subscript The pixel value of the input signal IS subjected to gradation processing using both the candidate Gk + 1 and the weighted average (internal division) using the value after the decimal point of the value [SS] of the selection signal SS is output, and the output signal OS is output. May be.

(3)
In the above-described embodiment, it has been described that the pixel values of the output signal OS are arranged in the column direction of the matrix with respect to the upper 6 bits of the pixel value of the input signal IS represented by 10 bits, for example. Here, the output signal OS may be output as a component of a matrix that is linearly interpolated by the gradation processing execution unit 25 with the lower 4 bits of the pixel value of the input signal IS. That is, in the column direction of the matrix, for example, the components of the matrix corresponding to the upper 6 bits of the pixel value of the input signal IS represented by 10 bits are arranged, and the upper 6 bits of the pixel value of the input signal IS are arranged. The matrix component and the matrix component for the value obtained by adding [1] to the upper 6 bits of the pixel value of the input signal IS (for example, the component one row below in FIG. 8) are the pixel values of the input signal IS. Are linearly interpolated using the value of the lower 4 bits and output as the output signal OS.

As a result, even if the size of the two-dimensional LUT 41 (see FIG. 8) is small, more appropriate gradation processing can be performed.
(4)
In the embodiment described above, the selection signal Sm for the image area Pm is output based on the average brightness value of the wide area image area Em. Here, the method of outputting the selection signal Sm is not limited to this method. For example, the selection signal Sm for the image area Pm may be output based on the maximum brightness value or the minimum brightness value of the wide area image area Em. The value [Sm] of the selection signal Sm may be the average brightness value, the maximum brightness value, or the minimum brightness value of the wide area image area Em.
For example, the selection signal Sm for the image region Pm may be output as follows. That is, an average brightness value is obtained for each image region Pm, and a provisional selection signal Sm ′ for each image region Pm is obtained from each average brightness value. Here, the provisional selection signal Sm ′ has the values of the subscript numbers of the gradation conversion curve candidates G1 to Gp as values. Further, for each image area included in the wide area image area Em, the value of the temporary selection signal Sm ′ is averaged to obtain the selection signal Sm of the image area Pm.

(5)
In the embodiment described above, the selection signal Sm for the image area Pm is output based on the average brightness value of the wide area image area Em. Here, the selection signal Sm for the image area Pm may be output based on a weighted average (weighted average) instead of a simple average of the wide area image area Em. The details are the same as those described with reference to FIG. 11 in the above [Second Embodiment]. The average brightness value of each image area constituting the wide area image area Em is obtained, and the average brightness value of the image area Pm is calculated. For the image areas Ps1, Ps2,... Having significantly different average brightness values, the weighting is reduced and the average brightness value of the wide area image area Em is obtained.
As a result, even when the wide area image region Em includes an area specific to brightness (for example, when the wide area image area Em includes a boundary between two objects having different brightness values), the selection signal Sm is output. On the other hand, the influence of the brightness value of the specific area is reduced, and an appropriate selection signal Sm is output.

(6)
The visual processing device 21 may further include a profile data creation unit that creates profile data that is a value stored in the two-dimensional LUT. Specifically, the profile data creation unit includes an image dividing unit 2 and a tone conversion curve deriving unit 10 in the visual processing device 1 (see FIG. 1). The set is stored in the two-dimensional LUT as profile data.
Further, each of the gradation conversion curves stored in the two-dimensional LUT may be associated with the spatially processed input signal IS. In this case, in the visual processing device 21, the image dividing unit 22, the selection signal deriving unit 23, and the selection signal correcting unit 24 may be replaced with a spatial processing unit that spatially processes the input signal IS.

[Fourth Embodiment]
A visual processing device 61 according to a fourth embodiment of the present invention will be described with reference to FIGS.
A visual processing device 61 shown in FIG. 22 is a device that performs visual processing such as spatial processing and gradation processing of an image signal. The visual processing device 61 constitutes an image processing device together with a device that performs color processing of an image signal in a device that handles images, such as a computer, a television, a digital camera, a mobile phone, a PDA, a printer, and a scanner.
The visual processing device 61 is a device that performs visual processing using an image signal and a blur signal obtained by performing spatial processing (blur filter processing) on the image signal, and has a feature in spatial processing.

Conventionally, when a blur signal is derived using pixels around a target pixel, if the peripheral pixel includes a pixel having a large density different from that of the target pixel, the blur signal is affected by a pixel having a different density. That is, when spatially processing pixels near the edge of an object in an image, pixels that are not originally edges are affected by the edge density. For this reason, for example, the generation of a pseudo contour is caused by this spatial processing.
Therefore, it is required to perform spatial processing in accordance with the content of the image. On the other hand, for example, Japanese Patent Laid-Open No. 10-75395 generates a plurality of blur signals having different degrees of blur, and outputs appropriate blur signals by combining or switching the respective blur signals. Accordingly, an object is to change the filter size of the spatial processing and suppress the influence of pixels having different densities.

On the other hand, in the above publication, a plurality of blur signals are created, and the respective blur signals are combined or switched, which increases the circuit scale or processing load in the apparatus.
Therefore, the visual processing device 61 according to the fourth embodiment of the present invention aims to output an appropriate blur signal and to reduce the circuit scale or processing load in the device.
<Visual processing device 61>
FIG. 22 shows a basic configuration of a visual processing device 61 that performs visual processing on an image signal (input signal IS) and outputs a visually processed image (output signal OS). The visual processing device 61 performs spatial processing on the brightness value of each pixel of the original image acquired as the input signal IS and outputs an unsharp signal US, and the input signal IS and unsharp signal for the same pixel. A visual processing unit 63 that performs visual processing of an original image using US and outputs an output signal OS is provided.

<Spatial processing unit 62>
The spatial processing of the spatial processing unit 62 will be described with reference to FIG. The spatial processing unit 62 acquires the pixel values of the target pixel 65 to be subjected to spatial processing and the pixels in the peripheral area of the target pixel 65 (hereinafter referred to as the peripheral pixel 66) from the input signal IS.
The peripheral pixel 66 is a pixel located in the peripheral region of the target pixel 65 and is a pixel included in the peripheral region of 9 pixels in the vertical direction and 9 pixels in the horizontal direction that spreads around the target pixel 65. Note that the size of the peripheral region is not limited to this case, and may be smaller or larger. Further, the peripheral pixel 66 is divided into a first peripheral pixel 67 and a second peripheral pixel 68 that are close to each other according to the distance from the target pixel 65. In FIG. 23, it is assumed that the first peripheral pixel 67 is a pixel included in an area of 5 pixels vertically and 5 pixels horizontally with the target pixel 65 as the center. Furthermore, the second peripheral pixel 68 is a pixel located around the first peripheral pixel 67.

The spatial processing unit 62 performs a filter operation on the target pixel 65. In the filter calculation, the pixel values of the target pixel 65 and the peripheral pixel 66 are weighted and averaged using a weight based on the difference and distance between the pixel values of the target pixel 65 and the peripheral pixel 66. The weighted average is calculated based on the following formula F = (Σ [Wij] * [Aij]) / (Σ [Wij]). Here, [Wij] is the weighting factor of the pixel located in the i-th row and j-th column in the target pixel 65 and the peripheral pixel 66, and [Aij] is the i-th row and j-th column in the target pixel 65 and the peripheral pixel 66. This is the pixel value of the pixel located in the eye. Further, “Σ” means that a total calculation is performed for each of the target pixel 65 and the peripheral pixel 66.
The weighting coefficient [Wij] will be described with reference to FIG. The weighting coefficient [Wij] is a value determined based on the difference in pixel value and the distance between the target pixel 65 and the peripheral pixel 66. More specifically, a smaller weight coefficient is given as the absolute value of the pixel value difference increases. Also, a smaller weighting factor is given as the distance increases.

For example, for the target pixel 65, the weighting coefficient [Wij] is the value [1].
Of the first peripheral pixels 67, the weight coefficient [Wij] is a value [1] for a pixel having a pixel value whose absolute value of the difference from the pixel value of the target pixel 65 is smaller than a predetermined threshold value. . Of the first peripheral pixels 67, the weight coefficient [Wij] is a value [1/2] for a pixel having a pixel value whose absolute value of the difference is larger than a predetermined threshold value. In other words, even the pixels included in the first peripheral pixel 67 have different weighting coefficients given according to the pixel values.
Of the second peripheral pixels 68, for a pixel having a pixel value whose absolute value of the difference from the pixel value of the target pixel 65 is smaller than a predetermined threshold, the weighting coefficient [Wij] is a value [1/2]. It is. Of the second peripheral pixels 68, the weight coefficient [Wij] is a value [1/4] for a pixel having a pixel value whose absolute value of the difference is larger than a predetermined threshold value. That is, even the pixels included in the second peripheral pixel 68 have different weighting coefficients given according to the pixel values. In addition, a smaller weight coefficient is given to the second peripheral pixel 68 whose distance from the target pixel 65 is larger than that of the first peripheral pixel 67.

Here, the predetermined threshold is a value [20/256 to 60/256] or the like with respect to the pixel value of the target pixel 65 that takes a value in the range of [0.0 to 1.0]. Value.
The weighted average calculated as described above is output as the unsharp signal US.
<Visual processing unit 63>
The visual processing unit 63 performs visual processing using the values of the input signal IS and the unsharp signal US for the same pixel. The visual processing performed here is processing such as contrast enhancement of the input signal IS or dynamic range compression. In contrast enhancement, a signal enhanced using a function that enhances the difference or ratio between the input signal IS and the unsharp signal US is added to the input signal IS to sharpen the image. In dynamic range compression, the unsharp signal US is subtracted from the input signal IS.

The processing in the visual processing unit 63 may be performed using a two-dimensional LUT that receives the input signal IS and the unsharp signal US and outputs the output signal OS.
<Visual processing method / program>
The above-described processing may be executed by a computer or the like as a visual processing program. The visual processing program is a program for causing a computer to execute the visual processing method described below.
The visual processing method includes a spatial processing step of performing spatial processing on the brightness value for each pixel of the original image acquired as the input signal IS and outputting an unsharp signal US, and an input signal IS and an unsharp signal US for the same pixel. And a visual processing step for performing visual processing of the original image and outputting an output signal OS.

In the spatial processing step, the weighted average described in the description of the spatial processing unit 62 is performed for each pixel of the input signal IS, and the unsharp signal US is output. Details are omitted because they have been described above.
In the visual processing step, the visual processing described in the description of the visual processing unit 63 is performed using the input signal IS and the unsharp signal US for the same pixel, and the output signal OS is output. Details are omitted because they have been described above.
<effect>
The effect of the visual processing by the visual processing device 61 will be described with reference to FIGS. FIG. 25A and FIG. 25B show processing by a conventional filter. FIG. 25B shows processing by the filter of the present invention.

FIG. 25A shows a state in which the peripheral pixels 66 include objects 71 having different densities. In the spatial processing of the target pixel 65, a smoothing filter having a predetermined filter coefficient is used. For this reason, the target pixel 65 that is not originally part of the object 71 is affected by the density of the object 71.
FIG. 25B shows the state of the spatial processing of the present invention. In the spatial processing of the present invention, each of the peripheral pixel 66 including the portion 66a including the object 71, the first peripheral pixel 67 not including the object 71, the second peripheral pixel 68 not including the object 71, and the target pixel 65, Spatial processing is performed using different weighting factors. For this reason, it is possible to suppress the influence of the spatially processed target pixel 65 from pixels with extremely different densities, and more appropriate spatial processing is possible.
Further, in the visual processing device 61, it is not necessary to create a plurality of blur signals as in JP-A-10-75395. For this reason, it becomes possible to reduce the circuit scale or processing load in the apparatus.

Further, the visual processing device 61 can substantially adaptively change the filter size of the spatial filter and the shape of the image referred to by the filter in accordance with the image content. For this reason, it is possible to perform spatial processing suitable for the image content.
<Modification>
(1)
The sizes of the peripheral pixel 66, the first peripheral pixel 67, the second peripheral pixel, and the like described above are merely examples, and other sizes may be used.
The weighting factor described above is an example and may be other. For example, when the absolute value of the pixel value difference exceeds a predetermined threshold, the weighting factor may be given as the value [0]. As a result, it is possible to eliminate the influence of the spatially processed target pixel 65 from pixels with extremely different densities. This has the effect of not over-enhancing the contrast in a part where the contrast is originally large to some extent in the application aiming at contrast enhancement.

The weighting factor may be given as a function value as shown below.
(1-a)
The value of the weighting coefficient may be given by a function having the absolute value of the difference between pixel values as a variable. For example, the function is such that the weighting factor is large (close to 1) when the absolute value of the pixel value difference is small, and the weighting factor is small (close to 0) when the absolute value of the pixel value difference is large. This is a function that monotonously decreases with respect to the absolute value of the difference between pixel values.
(1-b)
The value of the weighting coefficient may be given by a function using the distance from the target pixel 65 as a variable. For example, the function is such that the weighting factor is large (close to 1) when the distance from the target pixel 65 is short, and the weighting factor is small (close to 0) when the distance from the target pixel 65 is long. Is a monotonically decreasing function with respect to the distance.

In the above (1-a) and (1-b), the weight coefficient is given more continuously. For this reason, it is possible to give a more appropriate weighting coefficient as compared with the case of using a threshold, to suppress excessive contrast enhancement, to suppress generation of pseudo contours, and to perform processing with higher visual effect. Can be done.
(2)
The processing for each pixel described above may be performed in units of blocks including a plurality of pixels. Specifically, first, an average pixel value of a target block to be subjected to spatial processing and an average pixel value of peripheral blocks around the target block are calculated. Further, each average pixel value is weighted and averaged using the same weighting factor as described above. As a result, the average pixel value of the target block is further spatially processed.

In such a case, the spatial processing unit 62 can be used as the selection signal deriving unit 13 (see FIG. 6) or the selection signal deriving unit 23 (see FIG. 19). In this case, it is the same as described in [Second Embodiment] <Modification> (6) or [Third Embodiment] <Modification> (5).
This will be described with reference to FIGS.
"Constitution"
FIG. 26 is a block diagram illustrating a configuration of a visual processing device 961 that performs the processing described with reference to FIGS. 22 to 25 in units of blocks including a plurality of pixels.
The visual processing device 961 includes an image dividing unit 964 that divides an image input as an input signal IS into a plurality of image blocks, a spatial processing unit 962 that performs spatial processing for each divided image block, and an input signal IS and a space. The visual processing unit 963 performs visual processing using the spatial processing signal US2 that is the output of the processing unit 962.

The image dividing unit 964 divides an image input as the input signal IS into a plurality of image blocks. Further, a processing signal US1 including a feature parameter for each divided image block is derived. The feature parameter is, for example, a parameter that represents the feature of an image for each divided image block, and is, for example, an average value (simple average, weighted average, etc.) or a representative value (maximum value, minimum value, median value, etc.). is there.
The spatial processing unit 962 acquires a processing signal US1 including a feature parameter for each image block, and performs spatial processing.
The spatial processing of the spatial processing unit 962 will be described using FIG. FIG. 27 shows an input signal IS divided into image blocks including a plurality of pixels. Here, each image block is divided into regions including 9 pixels of 3 vertical pixels and 3 horizontal pixels. Note that this division method is an example, and is not limited to such a division method. Further, in order to sufficiently exhibit the visual processing effect, it is preferable to generate the spatial processing signal US2 for a considerably wide area.

The spatial processing unit 962 acquires the characteristic parameters of the target image block 965 to be subjected to spatial processing and the respective peripheral image blocks included in the peripheral region 966 located around the target image block 965 from the processing signal US1.
The peripheral area 966 is an area located around the target image block 965, and is an area of five vertical blocks and five horizontal blocks that spread around the target image block 965. Note that the size of the peripheral region 966 is not limited to this case, and may be smaller or larger. Further, the peripheral area 966 is divided into a first peripheral area 967 and a second peripheral area 968 that are close to each other according to the distance from the target image block 965.
In FIG. 27, the first peripheral area 967 is assumed to be an area of three vertical blocks and three horizontal blocks centering on the target image block 965. Furthermore, the second peripheral area 968 is assumed to be an area located around the first peripheral area 967.

The spatial processing unit 962 performs a filter operation on the feature parameter of the target image block 965.
In the filter calculation, the feature parameter values of the target image block 965 and the peripheral image blocks in the peripheral region 966 are weighted averaged. Here, the weight of the weighted average is determined based on the distance between the target image block 965 and the peripheral image block and the difference in the characteristic parameter values.
More specifically, the weighted average is calculated based on the following formula F = (Σ [Wij] * [Aij]) / (Σ [Wij]).
Here, [Wij] is a weighting factor for the image block located in the i-th row and j-th column in the target image block 965 and the peripheral region 966, and [Aij] is i in the target image block 965 and the peripheral region 966. This is the value of the feature parameter of the image block located in the row j column. Further, “Σ” means that a total calculation is performed for each image block of the target image block 965 and the peripheral region 966.

The weighting coefficient [Wij] will be described with reference to FIG.
The weighting coefficient [Wij] is a value determined based on the distance between the target image block 965 and the surrounding image blocks in the surrounding area 966 and the difference between the characteristic parameter values. More specifically, a smaller weight coefficient is given as the absolute value of the difference between the characteristic parameter values is larger. Also, a smaller weighting factor is given as the distance increases.
For example, for the target image block 965, the weighting coefficient [Wij] is the value [1].
In the first peripheral region 967, for a peripheral image block having a feature parameter value whose absolute value of a difference from the feature parameter value of the target image block 965 is smaller than a predetermined threshold, the weighting coefficient [Wij] is , Value [1]. In the first peripheral region 967, the weight coefficient [Wij] is a value [1/2] for a peripheral image block having a feature parameter value whose absolute value of the difference is larger than a predetermined threshold value. That is, even in the peripheral image block included in the first peripheral region 967, the weighting coefficient given according to the value of the characteristic parameter is different.

In the second peripheral area 968, for a peripheral image block having a feature parameter value whose absolute value of the difference from the feature parameter value of the target image block 965 is smaller than a predetermined threshold, the weighting coefficient [Wij] is , Value [1/2]. In the second peripheral area 968, for a peripheral image block having a characteristic parameter value whose absolute value of the difference is larger than a predetermined threshold, the weighting coefficient [Wij] is a value [1/4]. That is, even in the peripheral image block included in the second peripheral area 968, the weighting coefficient given according to the value of the characteristic parameter is different. Further, a smaller weighting factor is given to the second peripheral area 968 where the distance from the target image block 965 is larger than the first peripheral area 967.
Here, the predetermined threshold is a value [20/256 to 60/256] or the like for the feature parameter value of the target image block 965 taking a value in the range of [0.0 to 1.0]. It is a magnitude value.

The weighted average calculated as described above is output as the spatial processing signal US2.
The visual processing unit 963 performs visual processing similar to that of the visual processing unit 63 (see FIG. 22). However, the difference from the visual processing unit 63 is that, instead of the unsharp signal US, the spatial processing signal US2 of the target image block including the target pixel to be subjected to visual processing is used. The processing in the visual processing unit 963 may be processed in batches for each target image block including the target pixel, but is processed by switching the spatial processing signal US2 in the order of the pixels acquired from the input signal IS. Also good.
The above processing is performed for all the pixels included in the input signal IS.
"effect"
In the processing of the spatial processing unit 962, processing in units of image blocks is performed. For this reason, the processing amount of the spatial processing unit 962 can be reduced, and higher-speed visual processing can be realized. In addition, the hardware scale can be reduced.

<Modification>
In the above description, the processing is performed in units of square blocks. Here, the shape of the block may be arbitrary.
Further, the above-described weighting factor, threshold value, and the like can be appropriately changed.
Here, some values of the weighting coefficient may be the value [0]. In this case, it is the same as making the shape of the peripheral region 966 an arbitrary shape.
Further, although it has been described that the spatial processing unit 962 performs spatial processing using the feature parameters of the target image block 965 and the peripheral region 966, the spatial processing is performed using feature parameters of only the peripheral region 966. May be. That is, the weight of the target image block 965 may be the value [0] in the weighted average weight of the spatial processing.

(3)
The processing in the visual processing unit 63 is not limited to the above. For example, the visual processing unit 63 uses the value A of the input signal IS, the value B of the unsharp signal US, the dynamic range compression function F4, and the enhancement function F5 to obtain the following expression C = F4 (A) * F5 (A / B ) May be output as the value of the output signal OS. Here, the dynamic range compression function F4 is a monotonically increasing function such as an upward convex power function, and is represented by, for example, F4 (x) = x ^ γ (0 <γ <1). The enhancement function F5 is a power function, and is expressed as, for example, F5 (x) = x ^ α (0 <α ≦ 1).
When such processing is performed in the visual processing unit 63, if an appropriate unsharp signal US output by the spatial processing unit 62 of the present invention is used, the dynamic range of the input signal IS is compressed and the local range is reduced. The contrast can be enhanced.

On the other hand, when the unsharp signal US is not appropriate and there is too little blur, it is possible to enhance the contrast appropriately although it is edge enhancement. If there is too much blur, contrast can be enhanced, but dynamic range compression cannot be performed properly.
[Fifth Embodiment]
As the fifth embodiment of the present invention, application examples of the visual processing device, the visual processing method, and the visual processing program described in the first to fourth embodiments and a system using the visual processing apparatus will be described.
A visual processing device is a device that performs built-in or connected image processing devices such as computers, televisions, digital cameras, mobile phones, and PDAs, and performs image gradation processing, and is realized as an integrated circuit such as an LSI. Is done.
More specifically, each functional block of the above embodiment may be individually made into one chip, or may be made into one chip so as to include a part or all. Note that the name used here is LSI, but it may also be called IC, system LSI, super LSI, or ultra LSI depending on the degree of integration.

Further, the method of circuit integration is not limited to LSI, and implementation with a dedicated circuit or a general-purpose processor is also possible. An FPGA (Field Programmable Gate Array) that can be programmed after manufacturing the LSI or a reconfigurable processor that can reconfigure the connection and setting of the circuit cells inside the LSI may be used.
Further, if integrated circuit technology comes out to replace LSI's as a result of the advancement of semiconductor technology or a derivative other technology, it is naturally also possible to carry out function block integration using this technology. Biotechnology can be applied.
Processing of each block of Drawing 1, Drawing 6, Drawing 19, Drawing 22, and Drawing 26 is performed by a central processing unit (CPU) with which a visual processing unit is provided, for example. In addition, a program for performing each processing is stored in a storage device such as a hard disk or a ROM, and is read out and executed in the ROM or the RAM. Further, the two-dimensional LUT referred to in the gradation processing execution units 14 and 25 in FIGS. 6 and 19 is stored in a storage device such as a hard disk or ROM, and is referred to as necessary. Further, the two-dimensional LUT may be provided from a two-dimensional LUT providing device that is directly connected to the visual processing device or indirectly connected via a network. The same applies to the one-dimensional LUT referred to in the gradation processing execution unit 44 of FIG.

In addition, the visual processing device may be a device that performs gradation processing of an image for each frame (for each field) built in or connected to a device that handles moving images.
In each visual processing device, the visual processing method described in the first to fourth embodiments is executed.
The visual processing program is stored in a storage device such as a hard disk or ROM in a device that handles images, such as a computer, television, digital camera, mobile phone, PDA, etc., and executes gradation processing of the image. For example, the program is provided via a recording medium such as a CD-ROM or via a network.
In the above embodiment, it has been described that the processing is performed on the brightness value of each pixel. Here, the present invention does not depend on the color space of the input signal IS. That is, in the processing in the above embodiment, the input signal IS is expressed in the YCbCr color space, YUV color space, Lab color space, Luv color space, YIQ color space, XYZ color space, YPbPr color space, RGB color space, and the like. In this case, the present invention can be similarly applied to the luminance and brightness of each color space.

Further, when the input signal IS is expressed in the RGB color space, the processing in the above embodiment may be performed independently for each component of RGB.
[Sixth Embodiment]
As a sixth embodiment of the present invention, an application example of the visual processing device, visual processing method, and visual processing program described above and a system using the same will be described with reference to FIGS.
FIG. 29 is a block diagram showing an overall configuration of a content supply system ex100 that implements a content distribution service. The communication service providing area is divided into desired sizes, and base stations ex107 to ex110, which are fixed wireless stations, are installed in each cell.
The content supply system ex100 includes, for example, a computer ex111, a PDA (personal digital assistant) ex112, a camera ex113, a mobile phone ex114, a camera via the Internet ex101, the Internet service provider ex102, the telephone network ex104, and the base stations ex107 to ex110. Each device such as the attached mobile phone ex115 is connected.

However, the content supply system ex100 is not limited to the combination as shown in FIG. 29, and any combination may be connected. Also, each device may be directly connected to the telephone network ex104 without going through the base stations ex107 to ex110 which are fixed wireless stations.
The camera ex113 is a device capable of shooting a moving image such as a digital video camera. The mobile phone is a PDC (Personal Digital Communications) system, a CDMA (Code Division Multiple Access) system, a W-CDMA (Wideband-Code Division Multiple Access) system, or a GSM (Global System for Mobile Communications) system mobile phone, Alternatively, PHS (Personal Handyphone System) or the like may be used.
Further, the streaming server ex103 is connected from the camera ex113 through the base station ex109 and the telephone network ex104, and live distribution based on the encoded data transmitted by the user using the camera ex113 can be performed. The encoding processing of the captured data may be performed by the camera ex113 or may be performed by a server or the like that performs data transmission processing. The moving image data shot by the camera ex116 may be transmitted to the streaming server ex103 via the computer ex111. The camera ex116 is a device such as a digital camera that can shoot still images and moving images. In this case, the moving image data may be encoded by the camera ex116 or the computer ex111. The encoding process is performed in the LSI ex117 included in the computer ex111 and the camera ex116. Note that image encoding / decoding software may be incorporated in some storage medium (CD-ROM, flexible disk, hard disk, etc.) that is a recording medium readable by the computer ex111 or the like. Furthermore, you may transmit moving image data with the mobile phone ex115 with a camera. The moving image data at this time is data encoded by the LSI included in the mobile phone ex115.

  In the content supply system ex100, the content (for example, a video image of music live) captured by the user with the camera ex113, the camera ex116, and the like is encoded and transmitted to the streaming server ex103, while the streaming server ex103. Distributes the content data to the requested client. Examples of the client include a computer ex111, a PDA ex112, a camera ex113, and a mobile phone ex114 that can decode the encoded data. In this way, the content supply system ex100 can receive and play back the encoded data at the client, and can also receive a private broadcast by receiving, decoding, and playing back at the client in real time. It is a system that becomes possible.

When displaying content, the visual processing device, visual processing method, and visual processing program described in the above embodiment may be used. For example, the computer ex111, the PDA ex112, the camera ex113, the mobile phone ex114, and the like may be provided with the visual processing device described in the above embodiment and realize a visual processing method and a visual processing program.
Further, the streaming server ex103 may provide profile data to the visual processing device via the Internet ex101. Furthermore, there may be a plurality of streaming servers ex103 that provide different profile data. Further, the streaming server ex103 may create a profile. As described above, when the visual processing device can acquire the profile data via the Internet ex101, the visual processing device does not need to store the profile data used for the visual processing in advance, and the storage capacity of the visual processing device is reduced. It is also possible to do. Further, since profile data can be acquired from a plurality of servers connected via the Internet ex101, different visual processing can be realized.

A mobile phone will be described as an example.
FIG. 30 is a diagram illustrating a mobile phone ex115 including the visual processing device according to the embodiment. The mobile phone ex115 includes an antenna ex201 for transmitting and receiving radio waves to and from the base station ex110, a video from a CCD camera, a camera unit ex203 capable of taking a still image, a video shot by the camera unit ex203, and an antenna ex201. A display unit ex202 such as a liquid crystal display that displays data obtained by decoding received video and the like, a main body unit composed of a group of operation keys ex204, an audio output unit ex208 such as a speaker for audio output, and audio input To store encoded data or decoded data such as a voice input unit ex205 such as a microphone, captured video or still image data, received mail data, video data or still image data, etc. Recording media ex207 and mobile phone ex115 with recording media ex207 And a slot portion ex206 to ability. The recording medium ex207 stores a flash memory element, which is a kind of EEPROM (Electrically Erasable and Programmable Read Only Memory), which is a nonvolatile memory that can be electrically rewritten and erased, in a plastic case such as an SD card.

Further, the cellular phone ex115 will be described with reference to FIG. The mobile phone ex115 controls the main control unit ex311 which controls the respective units of the main body unit including the display unit ex202 and the operation key ex204. The power supply circuit unit ex310, the operation input control unit ex304, and the image encoding Unit ex312, camera interface unit ex303, LCD (Liquid Crystal Display) control unit ex302, image decoding unit ex309, demultiplexing unit ex308, recording / reproducing unit ex307, modulation / demodulation circuit unit ex306, and audio processing unit ex305 via a synchronization bus ex313 Are connected to each other.
When the end of call and the power key are turned on by a user operation, the power supply circuit ex310 starts up the camera-equipped digital mobile phone ex115 in an operable state by supplying power from the battery pack to each unit. .

The cellular phone ex115 converts the voice signal collected by the voice input unit ex205 in the voice call mode into digital voice data by the voice processing unit ex305 based on the control of the main control unit ex311 including a CPU, a ROM, a RAM, and the like. The modulation / demodulation circuit unit ex306 performs spread spectrum processing, the transmission / reception circuit unit ex301 performs digital analog conversion processing and frequency conversion processing, and then transmits the result via the antenna ex201. In addition, the cellular phone ex115 amplifies the received signal received by the antenna ex201 in the voice call mode, performs frequency conversion processing and analog-digital conversion processing, performs spectrum despreading processing by the modulation / demodulation circuit unit ex306, and analog audio by the voice processing unit ex305. After conversion into a signal, this is output via the audio output unit ex208.
Further, when an e-mail is transmitted in the data communication mode, text data of the e-mail input by operating the operation key ex204 of the main body is sent to the main control unit ex311 via the operation input control unit ex304. The main control unit ex311 performs spread spectrum processing on the text data in the modulation / demodulation circuit unit ex306, performs digital analog conversion processing and frequency conversion processing in the transmission / reception circuit unit ex301, and then transmits the text data to the base station ex110 via the antenna ex201.

When transmitting image data in the data communication mode, the image data captured by the camera unit ex203 is supplied to the image encoding unit ex312 via the camera interface unit ex303. When image data is not transmitted, the image data captured by the camera unit ex203 can be directly displayed on the display unit ex202 via the camera interface unit ex303 and the LCD control unit ex302.
The image encoding unit ex312 converts the image data supplied from the camera unit ex203 into encoded image data by compression encoding, and sends the encoded image data to the demultiplexing unit ex308. At the same time, the cellular phone ex115 sends the sound collected by the audio input unit ex205 during imaging by the camera unit ex203 to the demultiplexing unit ex308 as digital audio data via the audio processing unit ex305.

The demultiplexing unit ex308 multiplexes the encoded image data supplied from the image encoding unit ex312 and the audio data supplied from the audio processing unit ex305 by a predetermined method, and the resulting multiplexed data is a modulation / demodulation circuit unit Spread spectrum processing is performed in ex306, digital analog conversion processing and frequency conversion processing are performed in the transmission / reception circuit unit ex301, and then transmitted through the antenna ex201.
When receiving data of a moving image file linked to a homepage or the like in the data communication mode, the received signal received from the base station ex110 via the antenna ex201 is subjected to spectrum despreading processing by the modulation / demodulation circuit unit ex306, and the resulting multiplexing is obtained. Data is sent to the demultiplexing unit ex308.
In addition, in order to decode the multiplexed data received via the antenna ex201, the demultiplexing unit ex308 separates the multiplexed data to generate an encoded bitstream of image data and an encoded bitstream of audio data. The encoded image data is supplied to the image decoding unit ex309 via the synchronization bus ex313, and the audio data is supplied to the audio processing unit ex305.

Next, the image decoding unit ex309 generates reproduction moving image data by decoding the encoded bit stream of the image data, and supplies this to the display unit ex202 via the LCD control unit ex302. The moving image data included in the moving image file linked to the home page is displayed. At the same time, the audio processing unit ex305 converts the audio data into an analog audio signal, and then supplies the analog audio signal to the audio output unit ex208. Thus, for example, the audio data included in the moving image file linked to the home page is reproduced. The
In the above configuration, the image decoding unit ex309 may include the visual processing device of the above embodiment.
It should be noted that the present invention is not limited to the above-described system, and recently, digital broadcasting using satellites and terrestrial waves has become a hot topic. As shown in FIG. Methods and visual processing programs can be incorporated. Specifically, in the broadcasting station ex409, a coded bit stream of video information is transmitted to a communication or broadcasting satellite ex410 via radio waves. Receiving this, the broadcasting satellite ex410 transmits a radio wave for broadcasting, and receives the radio wave with a home antenna ex406 having a satellite broadcasting receiving facility, such as a television (receiver) ex401 or a set top box (STB) ex407. The device decodes the encoded bit stream and reproduces it. Here, a device such as the television (receiver) ex401 or the set-top box (STB) ex407 may include the visual processing device described in the above embodiment. Moreover, you may use the visual processing method of the said embodiment. Furthermore, a visual processing program may be provided. In addition, the visual processing device, the visual processing method, and the visual processing program described in the above embodiment are also applied to the playback device ex403 that reads and decodes the encoded bitstream recorded on the storage medium ex402 such as a CD or DVD that is a recording medium. It is possible to implement. In this case, the reproduced video signal is displayed on the monitor ex404. In addition, the visual processing device, the visual processing method, and the visual processing program described in the above embodiment are mounted in a set-top box ex407 connected to a cable ex405 for cable television or an antenna ex406 for satellite / terrestrial broadcasting. A configuration of reproducing on a television monitor ex408 can also be considered. At this time, the visual processing device described in the above embodiment may be incorporated in the television instead of the set top box. It is also possible to receive a signal from the satellite ex410 or the base station ex107 by the car ex412 having the antenna ex411 and reproduce the moving image on a display device such as the car navigation ex413 that the car ex412 has.

Furthermore, an image signal can be encoded and recorded on a recording medium. Specific examples include a recorder ex420 such as a DVD recorder that records image signals on a DVD disk ex421 and a disk recorder that records data on a hard disk. Further, it can be recorded on the SD card ex422. If the recorder ex420 includes the decoding device of the above embodiment, the image signal recorded on the DVD disc ex421 or the SD card ex422 can be interpolated and reproduced and displayed on the monitor ex408.
For example, the configuration of the car navigation ex413 may be a configuration excluding the camera unit ex203, the camera interface unit ex303, and the image encoding unit ex312 in the configuration illustrated in FIG. ) Ex401 can also be considered.

In addition to the transmission / reception type terminal having both the encoder and the decoder, the terminal such as the mobile phone ex114 has three mounting formats, that is, a transmitting terminal having only an encoder and a receiving terminal having only a decoder. Can be considered.
As described above, the visual processing device, the visual processing method, and the visual processing program described in the above embodiment can be used in any of the devices and systems described above, and the effects described in the above embodiment can be obtained.
[Appendix]
The present invention described in the above embodiment can also be expressed as follows.
<Contents of supplementary notes>
(Appendix 1)
Image region dividing means for dividing the input image signal into a plurality of image regions;
Means for deriving gradation conversion characteristics for each image area, wherein the target is obtained by using gradation characteristics of a target image area from which the gradation conversion characteristics are derived and a peripheral image area of the target image area; Gradation conversion characteristic deriving means for deriving the gradation conversion characteristic of the image area;
Gradation processing means for performing gradation processing of the image signal based on the derived gradation conversion characteristics;
A visual processing device comprising:

(Appendix 2)
The gradation conversion characteristic is a gradation conversion curve,
The gradation conversion characteristic deriving unit includes a histogram generation unit that generates a histogram using the gradation characteristic, and a gradation curve generation unit that generates the gradation conversion curve based on the generated histogram. ing,
The visual processing device according to attachment 1.
(Appendix 3)
The gradation conversion characteristic is a selection signal for selecting one gradation conversion table from among a plurality of gradation conversion tables for gradation-processing the image signal,
The gradation processing means has the plurality of gradation conversion tables as a two-dimensional LUT.
The visual processing device according to attachment 1.

(Appendix 4)
The two-dimensional LUT stores the plurality of gradation conversion tables in the order in which the value of the image signal subjected to gradation processing with respect to the value of the selection signal monotonously increases or decreases monotonously for all values of the image signal. ing,
The visual processing device according to attachment 3.
(Appendix 5)
The two-dimensional LUT can be changed by registering profile data.
The visual processing device according to attachment 3 or 4.
(Appendix 6)
The value of the selection signal is derived as a feature amount of an individual selection signal that is a selection signal derived for each of the target image region and the peripheral image region.
The visual processing device according to any one of appendices 3 to 5.

(Appendix 7)
The selection signal is derived based on a gradation characteristic feature amount that is a feature amount derived using gradation characteristics of the target image region and the peripheral image region.
The visual processing device according to any one of appendices 3 to 5.
(Appendix 8)
The gradation processing means includes gradation processing execution means for executing gradation processing of the target image area using the gradation conversion table selected by the selection signal, and gradation of the image signal subjected to the gradation processing. Means for correcting a tone, the target pixel based on the gradation processing table selected for an image area including the target pixel to be corrected and an image area adjacent to the image area including the target pixel Correction means for correcting the gradation of
The visual processing device according to any one of appendices 3 to 7.

(Appendix 9)
The gradation processing means corrects the selection signal and derives a correction selection signal for selecting a gradation processing table for each pixel of the image signal; and the gradation selected by the correction selection signal Gradation processing execution means for executing gradation processing of the image signal using a conversion table;
The visual processing device according to any one of appendices 3 to 7.
(Appendix 10)
An image region dividing step for dividing the input image signal into a plurality of image regions;
A step of deriving gradation conversion characteristics for each of the image areas, wherein the target is obtained using gradation characteristics of a target image area from which the gradation conversion characteristics are derived and a peripheral image area of the target image area; A gradation conversion characteristic deriving step for deriving the gradation conversion characteristic of the image region;
A gradation processing step for performing gradation processing of the image signal based on the derived gradation conversion characteristics;
A visual processing method comprising:

(Appendix 11)
The gradation conversion characteristic is a gradation conversion curve,
The gradation conversion characteristic deriving step includes a histogram creation step of creating a histogram using the gradation characteristic, and a gradation curve creation step of creating the gradation conversion curve based on the created histogram. ing,
The visual processing method according to attachment 10.
(Appendix 12)
The gradation conversion characteristic is a selection signal for selecting one gradation conversion table from among a plurality of gradation conversion tables for gradation-processing the image signal,
The gradation processing step includes a gradation processing execution step of performing gradation processing of the target image region using the gradation conversion table selected by the selection signal, and a gradation of the image signal subjected to the gradation processing. Correcting the tone, the target pixel based on the gradation processing table selected for the image region including the target pixel to be corrected and the image region adjacent to the image region including the target pixel A correction step for correcting the gradation of
The visual processing method according to attachment 10.

(Appendix 13)
The gradation conversion characteristic is a selection signal for selecting one gradation conversion table from among a plurality of gradation conversion tables for gradation-processing the image signal,
The gradation processing step corrects the selection signal and derives a correction selection signal for selecting a gradation processing table for each pixel of the image signal, and the gradation selected by the correction selection signal A gradation processing execution step for performing gradation processing of the image signal using a conversion table;
The visual processing method according to attachment 10.
(Appendix 14)
A visual processing program for performing a visual processing method by a computer,
The visual processing program is stored in a computer.
An image region dividing step for dividing the input image signal into a plurality of image regions;
A step of deriving gradation conversion characteristics for each of the image areas, wherein the target is obtained using gradation characteristics of a target image area from which the gradation conversion characteristics are derived and a peripheral image area of the target image area; A gradation conversion characteristic deriving step for deriving the gradation conversion characteristic of the image region;
A gradation processing step for performing gradation processing of the image signal based on the derived gradation conversion characteristics;
A visual processing method comprising:
Visual processing program.

(Appendix 15)
The gradation conversion characteristic is a gradation conversion curve,
The gradation conversion characteristic deriving step includes a histogram creation step of creating a histogram using the gradation characteristic, and a gradation curve creation step of creating the gradation conversion curve based on the created histogram. ing,
The visual processing program according to attachment 14.
(Appendix 16)
The gradation conversion characteristic is a selection signal for selecting one gradation conversion table from among a plurality of gradation conversion tables for gradation-processing the image signal,
The gradation processing step includes a gradation processing execution step of performing gradation processing of the target image region using the gradation conversion table selected by the selection signal, and a gradation of the image signal subjected to the gradation processing. Correcting the tone, the target pixel based on the gradation processing table selected for the image region including the target pixel to be corrected and the image region adjacent to the image region including the target pixel A correction step for correcting the gradation of
The visual processing program according to attachment 14.

(Appendix 17)
The gradation conversion characteristic is a selection signal for selecting one gradation conversion table from among a plurality of gradation conversion tables for gradation-processing the image signal,
The gradation processing step corrects the selection signal and derives a correction selection signal for selecting a gradation processing table for each pixel of the image signal, and the gradation selected by the correction selection signal A gradation processing execution step for performing gradation processing of the image signal using a conversion table;
The visual processing program according to attachment 14.
(Appendix 18)
The gradation processing means has parameter output means for outputting a curve parameter of a gradation conversion curve for gradation processing of the image signal based on the gradation conversion characteristics, and the gradation conversion specification And gradation processing the image signal using the gradation conversion curve specified based on the curve parameter and
The visual processing device according to attachment 1.

(Appendix 19)
The parameter output means is a lookup table that stores a relationship between the gradation conversion characteristics and the curve parameters.
The visual processing device according to appendix 18.
(Appendix 20)
The curve parameter includes a value of the gradation-processed image signal with respect to a predetermined value of the image signal.
The visual processing device according to appendix 18 or 19.
(Appendix 21)
The curve parameter includes an inclination of the gradation conversion curve in a predetermined section of the image signal.
The visual processing device according to any one of appendices 18 to 20.

(Appendix 22)
The curve parameter includes coordinates of at least one point through which the gradation conversion curve passes.
The visual processing device according to any one of appendices 18 to 21.
(Appendix 23)
A means for performing spatial processing for each of a plurality of image regions in an input image signal to derive a spatial processing signal, wherein the spatial processing includes a target image region that is a target of the spatial processing and a peripheral image of the target image region Spatial processing means for performing weighted averaging of the gradation characteristics of the target image area and the surrounding image area using weighting based on a difference in gradation characteristics with the area;
Visual processing means for performing visual processing of the target image region based on the gradation characteristics of the target image region and the spatial processing signal;
A visual processing device comprising:

(Appendix 24)
The weighting decreases as the absolute value of the difference in gradation characteristics increases.
The visual processing device according to attachment 23.
(Appendix 25)
The weighting decreases as the distance between the target image area and the peripheral image area increases.
The visual processing device according to attachment 23 or 24.
(Appendix 26)
The image area is composed of a plurality of pixels,
The gradation characteristics of the target image area and the peripheral image area are determined as feature values of pixel values constituting each image area.
The visual processing device according to any one of appendices 23 to 25.

(Appendix 27)
Target image area determining means for determining a target image area from which to derive the gradation conversion characteristics from the input image signal;
A peripheral image region determining means for determining at least one peripheral image region including a plurality of pixels located around the target image region;
Gradation conversion characteristic deriving means for deriving the gradation conversion characteristic of the target image area using the peripheral image data of the peripheral image area;
Gradation processing means for performing gradation processing of an image signal of the target image area based on the derived gradation conversion characteristics;
A visual processing device comprising:

(Appendix 28)
A target image region determination step for determining a target image region from which the gradation conversion characteristics are derived from the input image signal;
A peripheral image region determining step for determining at least one peripheral image region including a plurality of pixels located around the target image region;
A gradation conversion characteristic deriving step for deriving the gradation conversion characteristic of the target image area using the peripheral image data of the peripheral image area;
A gradation processing step for performing gradation processing of an image signal of the target image area based on the derived gradation conversion characteristics;
A visual processing method comprising:

(Appendix 29)
A visual processing program for performing a visual processing method for performing visual processing of an input image signal using a computer,
The visual processing method includes:
A target image region determination step for determining a target image region from which the gradation conversion characteristics are derived from the input image signal;
A peripheral image region determining step for determining at least one peripheral image region including a plurality of pixels located around the target image region;
A gradation conversion characteristic deriving step for deriving the gradation conversion characteristic of the target image area using the peripheral image data of the peripheral image area;
A gradation processing step for performing gradation processing of an image signal of the target image area based on the derived gradation conversion characteristics;
A visual processing method comprising:
Visual processing program.

(Appendix 30)
A target image region determination unit that determines a target image region from which the gradation conversion characteristics are derived from the input image signal;
A peripheral image region determining unit that determines at least one peripheral image region including a plurality of pixels located around the target image region;
A gradation conversion characteristic deriving unit that derives the gradation conversion characteristic of the target image area using the peripheral image data of the peripheral image area;
A gradation processing unit that performs gradation processing of an image signal of the target image area based on the derived gradation conversion characteristics;
A semiconductor device comprising:

<Explanation of Supplementary Notes>
The visual processing device according to attachment 1 includes image region dividing means, gradation conversion characteristic deriving means, and gradation processing means. The image area dividing means divides the input image signal into a plurality of image areas. The gradation conversion characteristic deriving means is a means for deriving the gradation conversion characteristic for each image area, and calculates the gradation characteristic between the target image area from which the gradation conversion characteristic is derived and the peripheral image area of the target image area. To derive the gradation conversion characteristics of the target image area. The gradation processing means performs gradation processing of the image signal based on the derived gradation conversion characteristics.
Here, the gradation conversion characteristic is a characteristic of gradation processing for each image region. The gradation characteristics are pixel values such as brightness and brightness for each pixel, for example.
In the visual processing device of the present invention, when determining the gradation conversion characteristics for each image area, not only the gradation characteristics for each image area but also the gradation characteristics of a wide image area including the peripheral image areas are used. Make a decision. For this reason, it is possible to add a spatial processing effect to the gradation processing for each image region, and it is possible to realize gradation processing that further improves the visual effect.

The visual processing device according to attachment 2 is the visual processing device according to attachment 1, in which the gradation conversion characteristic is a gradation conversion curve. The gradation conversion characteristic deriving unit includes a histogram generation unit that generates a histogram using the gradation characteristic, and a gradation curve generation unit that generates a gradation conversion curve based on the generated histogram.
Here, the histogram is, for example, a distribution with respect to gradation characteristics of pixels included in the target image area and the peripheral image area. For example, the gradation curve creating means sets a cumulative curve obtained by accumulating histogram values as a gradation conversion curve.
In the visual processing device of the present invention, when creating a histogram, the histogram is created using not only the gradation characteristics for each image area but also the wide-range gradation characteristics including the surrounding image areas. For this reason, it is possible to increase the number of divisions of the image signal and reduce the size of the image area, and to suppress the generation of pseudo contour due to gradation processing. Further, it is possible to prevent the boundary of the image area from being unnaturally conspicuous.

The visual processing device according to attachment 3 is the visual processing device according to attachment 1, wherein the gradation conversion characteristic is one gradation conversion table among a plurality of gradation conversion tables for gradation processing of the image signal. Is a selection signal for selecting. The gradation processing means has a plurality of gradation conversion tables as a two-dimensional LUT.
Here, the gradation conversion table is, for example, a look-up table (LUT) that stores pixel values of an image signal subjected to gradation processing with respect to pixel values of the image signal.
For example, the selection signal has a value assigned to one gradation conversion table selected from values assigned to each of the plurality of gradation conversion tables. The gradation processing means outputs the pixel value of the image signal subjected to gradation processing with reference to the two-dimensional LUT from the value of the selection signal and the pixel value of the image signal.

In the visual processing device of the present invention, gradation processing is performed with reference to a two-dimensional LUT. For this reason, it is possible to speed up the gradation processing. Also, since gradation processing is performed by selecting one gradation conversion table from a plurality of gradation conversion tables, appropriate gradation processing can be performed.
The visual processing device according to appendix 4 is the visual processing device according to appendix 3, wherein the two-dimensional LUT has a value of the image signal subjected to gradation processing with respect to the value of the selection signal in all values of the image signal. A plurality of gradation conversion tables are stored in the order of monotone increase or monotone decrease.
In the visual processing device of the present invention, for example, the value of the selection signal indicates the degree of gradation conversion.
The visual processing device according to attachment 5 is the visual processing device according to attachment 3 or 4, and the two-dimensional LUT can be changed by registering profile data.

Here, the profile data is data stored in the two-dimensional LUT and includes, for example, pixel values of the image signal subjected to gradation processing as elements.
In the visual processing device of the present invention, by changing the two-dimensional LUT, it is possible to variously change the characteristics of gradation processing without changing the hardware configuration.
The visual processing device according to attachment 6 is the visual processing device according to any one of attachments 3 to 5, wherein the value of the selection signal is derived for each of the target image region and the peripheral image region. It is derived as a feature quantity of the individual selection signal that is the selection signal.
Here, the feature amount of the individual selection signal is, for example, an average value (simple average or weighted average), maximum value, minimum value, or the like of the selection signal derived for each image region.
In the visual processing device of the present invention, the selection signal for the target image area is derived as the feature amount of the selection signal for the wide-area image area including the peripheral image area. For this reason, it is possible to add a spatial processing effect to the selection signal, and it is possible to prevent the boundary of the image area from being unnaturally conspicuous.

The visual processing device according to attachment 7 is the visual processing device according to any one of attachments 3 to 5, wherein the selection signal is derived using the gradation characteristics of the target image region and the peripheral image region. It is derived based on the gradation characteristic feature quantity which is a quantity.
Here, the gradation characteristic feature amount is, for example, an average value (simple average or weighted average), maximum value, or minimum value of gradation characteristics in a wide area between the target image area and the peripheral image area.
In the visual processing device of the present invention, the selection signal for the target image area is derived based on the gradation characteristic feature amount for the wide-area image area including the peripheral image area. For this reason, it is possible to add a spatial processing effect to the selection signal, and it is possible to prevent the boundary of the image area from being unnaturally conspicuous.
The visual processing device according to attachment 8 is the visual processing device according to any one of attachments 3 to 7, in which the gradation processing means includes gradation processing execution means and correction means. The gradation processing execution means executes gradation processing of the target image area using the gradation conversion table selected by the selection signal. The correction unit is a unit that corrects the gradation of the gradation-processed image signal, and is selected for the image region including the target pixel to be corrected and the image region adjacent to the image region including the target pixel. Based on the tone processing table, the gradation of the target pixel is corrected.

Here, the adjacent image region may be the same image region as the peripheral image region when the gradation conversion characteristic is derived, or may be a different image region. For example, the adjacent image regions are selected as three image regions having a short distance from the target pixel among the image regions adjacent to the image region including the target pixel.
For example, the correcting unit corrects the gradation of the image signal subjected to the gradation processing using the same gradation conversion table for each target image region. The correction of the target pixel is performed so that, for example, the influence of each gradation conversion table selected for the adjacent image region appears according to the position of the target pixel.
In the visual processing device of the present invention, it is possible to correct the gradation of the image signal for each pixel. For this reason, it is further prevented that the boundary of the image area stands out unnaturally, and the visual effect can be improved.

The visual processing device according to attachment 9 is the visual processing device according to any one of attachments 3 to 7, wherein the gradation processing means includes a correction means and a gradation processing execution means. The correction means corrects the selection signal and derives a correction selection signal for selecting a gradation processing table for each pixel of the image signal. The gradation processing execution means executes gradation processing of the image signal using the gradation conversion table selected by the correction selection signal.
For example, the correction unit corrects the selection signal derived for each target image region based on the pixel position and the selection signal derived for the image region adjacent to the target image region, and derives a selection signal for each pixel.
In the visual processing device of the present invention, it is possible to derive a selection signal for each pixel. For this reason, it is further prevented that the boundary of the image area stands out unnaturally, and the visual effect can be improved.

The visual processing method according to attachment 10 includes an image region dividing step, a gradation conversion characteristic deriving step, and a gradation processing step. The image region dividing step divides the input image signal into a plurality of image regions. The gradation conversion characteristic deriving step is a step of deriving the gradation conversion characteristic for each image area, and the gradation characteristics of the target image area from which the gradation conversion characteristic is derived and the surrounding image area of the target image area are calculated. To derive the gradation conversion characteristics of the target image area. In the gradation processing step, gradation processing of the image signal is performed based on the derived gradation conversion characteristics.
Here, the gradation conversion characteristic is a characteristic of gradation processing for each image region. The gradation characteristics are pixel values such as brightness and brightness for each pixel, for example.
In the visual processing method of the present invention, when determining the gradation conversion characteristics for each image area, not only the gradation characteristics for each image area but also the gradation characteristics of a wide image area including the peripheral image areas are used. Make a decision. For this reason, it is possible to add a spatial processing effect to the gradation processing for each image region, and it is possible to realize gradation processing with a higher visual effect.

The visual processing method according to attachment 11 is the visual processing method according to attachment 10, in which the gradation conversion characteristic is a gradation conversion curve. The gradation conversion characteristic deriving step includes a histogram creation step for creating a histogram using the gradation characteristics, and a gradation curve creation step for creating a gradation conversion curve based on the created histogram.
Here, the histogram is, for example, a distribution with respect to gradation characteristics of pixels included in the target image area and the peripheral image area. In the gradation curve creating step, for example, a cumulative curve obtained by accumulating histogram values is used as a gradation conversion curve.
In the visual processing method of the present invention, when creating a histogram, the histogram is created using not only the gradation characteristics for each image area but also the wide-range gradation characteristics including the peripheral image areas. For this reason, it is possible to increase the number of divisions of the image signal and reduce the size of the image area, and to suppress the generation of pseudo contour due to gradation processing. Further, it is possible to prevent the boundary of the image area from being unnaturally conspicuous.

The visual processing method according to attachment 12 is the visual processing method according to attachment 10, wherein the gradation conversion characteristic is one gradation conversion table among a plurality of gradation conversion tables for gradation processing of an image signal. Is a selection signal for selecting. The gradation processing step includes a gradation processing execution step and a correction step. In the gradation processing execution step, gradation processing of the target image area is executed using a gradation conversion table selected by the selection signal. The correction step is a step of correcting the gradation of the image signal that has been subjected to the gradation processing, and is performed for the image area including the target pixel to be corrected and an image area adjacent to the image area including the target pixel. Based on the tone processing table, the gradation of the target pixel is corrected.
Here, the gradation conversion table is, for example, a look-up table (LUT) that stores pixel values of an image signal subjected to gradation processing with respect to pixel values of the image signal. The adjacent image region may be the same image region as the peripheral image region when the gradation conversion characteristics are derived, or may be a different image region. For example, the adjacent image regions are selected as three image regions having a short distance from the target pixel among the image regions adjacent to the image region including the target pixel.

For example, the selection signal has a value assigned to one gradation conversion table selected from values assigned to each of the plurality of gradation conversion tables. In the gradation processing step, the pixel value of the image signal subjected to the gradation processing with reference to the LUT from the value of the selection signal and the pixel value of the image signal is output. In the correction step, for example, the gradation of the image signal subjected to gradation processing is corrected using the same gradation conversion table for each target image area. The correction of the target pixel is performed so that, for example, the influence of each gradation conversion table selected for the adjacent image region appears according to the position of the target pixel.
In the visual processing method of the present invention, gradation processing is performed with reference to the LUT. For this reason, it is possible to speed up the gradation processing. Also, since gradation processing is performed by selecting one gradation conversion table from a plurality of gradation conversion tables, appropriate gradation processing can be performed. Furthermore, the gradation of the image signal can be corrected for each pixel. For this reason, it is further prevented that the boundary of the image area stands out unnaturally, and the visual effect can be improved.

The visual processing method according to attachment 13 is the visual processing method according to attachment 10, wherein the gradation conversion characteristic is one gradation conversion table among a plurality of gradation conversion tables for gradation processing of an image signal. Is a selection signal for selecting. Further, the gradation processing step has a correction step and a gradation processing execution step. The correction step corrects the selection signal and derives a correction selection signal for selecting a gradation processing table for each pixel of the image signal. In the gradation processing execution step, gradation processing of the image signal is executed using a gradation conversion table selected by the correction selection signal.
Here, the gradation conversion table is, for example, a look-up table (LUT) that stores pixel values of an image signal subjected to gradation processing with respect to pixel values of the image signal.
For example, the selection signal has a value assigned to one gradation conversion table selected from values assigned to each of the plurality of gradation conversion tables. In the gradation processing step, the pixel value of the image signal subjected to gradation processing is output with reference to the two-dimensional LUT from the value of the selection signal and the pixel value of the image signal. In the correction step, for example, the selection signal derived for each target image region is corrected based on the pixel position and the selection signal derived for the image region adjacent to the target image region, and a selection signal for each pixel is derived.

In the visual processing method of the present invention, gradation processing is performed with reference to the LUT. For this reason, it is possible to speed up the gradation processing. Also, since gradation processing is performed by selecting one gradation conversion table from a plurality of gradation conversion tables, appropriate gradation processing can be performed. Furthermore, a selection signal can be derived for each pixel. For this reason, it is further prevented that the boundary of the image area stands out unnaturally, and the visual effect can be improved.
The visual processing program according to attachment 14 is a visual processing program that causes a computer to perform a visual processing method including an image region dividing step, a gradation conversion characteristic deriving step, and a gradation processing step. The image region dividing step divides the input image signal into a plurality of image regions. The gradation conversion characteristic deriving step is a step of deriving the gradation conversion characteristic for each image area, and the gradation characteristics of the target image area from which the gradation conversion characteristic is derived and the surrounding image area of the target image area are calculated. To derive the gradation conversion characteristics of the target image area. In the gradation processing step, gradation processing of the image signal is performed based on the derived gradation conversion characteristics.

Here, the gradation conversion characteristic is a characteristic of gradation processing for each image region. The gradation characteristics are pixel values such as brightness and brightness for each pixel, for example.
In the visual processing program of the present invention, when determining the gradation conversion characteristics for each image area, not only the gradation characteristics for each image area but also the gradation characteristics of a wide image area including the peripheral image areas are used. Make a decision. For this reason, it is possible to add a spatial processing effect to the gradation processing for each image region, and it is possible to realize gradation processing with a higher visual effect.
The visual processing program described in appendix 15 is the visual processing program described in appendix 14, and the gradation conversion characteristic is a gradation conversion curve. The gradation conversion characteristic deriving step includes a histogram creation step for creating a histogram using the gradation characteristics, and a gradation curve creation step for creating a gradation conversion curve based on the created histogram.

Here, the histogram is, for example, a distribution with respect to gradation characteristics of pixels included in the target image area and the peripheral image area. In the gradation curve creating step, for example, a cumulative curve obtained by accumulating histogram values is used as a gradation conversion curve.
In the visual processing program of the present invention, when creating a histogram, the histogram is created using not only the gradation characteristics for each image area but also the wide-range gradation characteristics including the peripheral image areas. For this reason, it is possible to increase the number of divisions of the image signal and reduce the size of the image area, and to suppress the generation of pseudo contour due to gradation processing. Further, it is possible to prevent the boundary of the image area from being unnaturally conspicuous.
The visual processing program according to attachment 16 is the visual processing program according to attachment 14, wherein the gradation conversion characteristic is one gradation conversion table among a plurality of gradation conversion tables for gradation processing of an image signal. Is a selection signal for selecting. The gradation processing step includes a gradation processing execution step and a correction step. In the gradation processing execution step, gradation processing of the target image area is executed using a gradation conversion table selected by the selection signal. The correction step is a step of correcting the gradation of the image signal that has been subjected to the gradation processing, and is performed for the image area including the target pixel to be corrected and an image area adjacent to the image area including the target pixel. Based on the tone processing table, the gradation of the target pixel is corrected.

Here, the gradation conversion table is, for example, a look-up table (LUT) that stores pixel values of an image signal subjected to gradation processing with respect to pixel values of the image signal. The adjacent image region may be the same image region as the peripheral image region when the gradation conversion characteristics are derived, or may be a different image region. For example, the adjacent image regions are selected as three image regions having a short distance from the target pixel among the image regions adjacent to the image region including the target pixel.
For example, the selection signal has a value assigned to one gradation conversion table selected from values assigned to each of the plurality of gradation conversion tables. In the gradation processing step, the pixel value of the image signal subjected to the gradation processing with reference to the LUT from the value of the selection signal and the pixel value of the image signal is output. In the correction step, for example, the gradation of the image signal subjected to gradation processing is corrected using the same gradation conversion table for each target image area. The correction of the target pixel is performed so that, for example, the influence of each gradation conversion table selected for the adjacent image region appears according to the position of the target pixel.

In the visual processing program of the present invention, gradation processing is performed with reference to the LUT. For this reason, it is possible to speed up the gradation processing. Also, since gradation processing is performed by selecting one gradation conversion table from a plurality of gradation conversion tables, appropriate gradation processing can be performed. Furthermore, the gradation of the image signal can be corrected for each pixel. For this reason, it is further prevented that the boundary of the image area stands out unnaturally, and the visual effect can be improved.
The visual processing program according to appendix 17 is the visual processing program according to appendix 14, wherein the gradation conversion characteristic is one gradation conversion table among a plurality of gradation conversion tables for gradation processing of an image signal. Is a selection signal for selecting. Further, the gradation processing step has a correction step and a gradation processing execution step. The correction step corrects the selection signal and derives a correction selection signal for selecting a gradation processing table for each pixel of the image signal. In the gradation processing execution step, gradation processing of the image signal is executed using a gradation conversion table selected by the correction selection signal.

Here, the gradation conversion table is, for example, a look-up table (LUT) that stores pixel values of an image signal subjected to gradation processing with respect to pixel values of the image signal.
For example, the selection signal has a value assigned to one gradation conversion table selected from values assigned to each of the plurality of gradation conversion tables. In the gradation processing step, the pixel value of the image signal subjected to gradation processing is output with reference to the two-dimensional LUT from the value of the selection signal and the pixel value of the image signal. In the correction step, for example, the selection signal derived for each target image region is corrected based on the pixel position and the selection signal derived for the image region adjacent to the target image region, and a selection signal for each pixel is derived.
In the visual processing program of the present invention, gradation processing is performed with reference to the LUT. For this reason, it is possible to speed up the gradation processing. Also, since gradation processing is performed by selecting one gradation conversion table from a plurality of gradation conversion tables, appropriate gradation processing can be performed. Furthermore, a selection signal can be derived for each pixel. For this reason, it is further prevented that the boundary of the image area stands out unnaturally, and the visual effect can be improved.

The visual processing device according to attachment 18 is the visual processing device according to attachment 1, in which the gradation processing means uses the gradation conversion characteristics for the gradation conversion curve for performing gradation processing on the image signal as gradation conversion characteristics. Parameter output means for outputting based on the above. The gradation processing means performs gradation processing on the image signal using the gradation conversion curve specified based on the gradation conversion specification and the curve parameter.
Here, the gradation conversion curve includes at least part of which is a straight line. The curve parameter is a parameter for distinguishing the gradation conversion curve from other gradation conversion curves, and includes, for example, coordinates on the gradation conversion curve, inclination of the gradation conversion curve, curvature, and the like. The parameter output means is, for example, a lookup table that stores curve parameters for gradation conversion characteristics, or an operation means for obtaining curve parameters by calculation such as curve approximation using curve parameters for predetermined gradation conversion characteristics.

In the visual processing device of the present invention, gradation processing is performed on an image signal according to gradation conversion characteristics. For this reason, it is possible to perform gradation processing more appropriately. Further, it is not necessary to store in advance the values of all the gradation conversion curves used for gradation processing, and gradation processing is performed by specifying the gradation conversion curve from the output curve parameters. For this reason, it is possible to reduce the storage capacity for storing the gradation conversion curve.
The visual processing device according to attachment 19 is the visual processing device according to attachment 18 in which the parameter output means is a look-up table that stores the relationship between the gradation conversion characteristics and the curve parameters.
The look-up table stores the relationship between gradation conversion characteristics and curve parameters. The gradation processing means performs gradation processing on the image signal using the specified gradation conversion curve.

In the visual processing device of the present invention, gradation processing is performed on an image signal according to gradation conversion characteristics. For this reason, it is possible to perform gradation processing more appropriately. Furthermore, it is not necessary to store in advance the values of all the gradation conversion curves used, and only the curve parameters are stored. For this reason, it is possible to reduce the storage capacity for storing the gradation conversion curve.
The visual processing device according to attachment 20 is the visual processing device according to attachment 18 or 19, wherein the curve parameter includes a value of the image signal subjected to gradation processing with respect to a predetermined value of the image signal.
The tone processing means uses the relationship between the predetermined value of the image signal and the value of the image signal to be visually processed to nonlinearly or linearly divide the value of the tone processed image signal included in the curve parameter. Then, the value of the gradation-processed image signal is derived.
In the visual processing device of the present invention, it is possible to perform gradation processing by specifying a gradation conversion curve from the value of a gradation-processed image signal for a predetermined value of the image signal.

The visual processing device according to attachment 21 is the visual processing device according to any one of attachments 18 to 20, wherein the curve parameter includes the gradient of the gradation conversion curve in a predetermined section of the image signal.
In the gradation processing means, the gradation conversion curve is specified by the slope of the gradation conversion curve in a predetermined section of the image signal. Furthermore, the value of the image signal subjected to the gradation process with respect to the value of the image signal is derived using the specified gradation conversion curve.
In the visual processing device of the present invention, it is possible to specify the gradation conversion curve based on the gradient of the gradation conversion curve in a predetermined section of the image signal and perform gradation processing.
The visual processing device according to attachment 22 is the visual processing device according to any one of attachments 18 to 21, wherein the curve parameter includes coordinates of at least one point through which the gradation conversion curve passes.
In the curve parameter, the coordinates of at least one point through which the gradation conversion curve passes are specified. That is, at least one point of the value of the image signal after gradation processing with respect to the value of the image signal is specified. The gradation processing means uses the relationship between the value of the specified image signal and the value of the image signal to be subjected to visual processing to add the value of the specified image signal after gradation processing in a nonlinear or linear manner. By dividing, the value of the image signal subjected to gradation processing is derived.

In the visual processing device of the present invention, the gradation conversion curve can be identified and the gradation processing can be performed by the coordinates of at least one point through which the gradation conversion curve passes.
The visual processing device according to attachment 23 includes spatial processing means and visual processing means. The spatial processing means is means for performing spatial processing for each of a plurality of image regions in the input image signal to derive a spatial processing signal. In spatial processing, weighting of gradation characteristics between the target image area and the surrounding image area is performed using weighting based on a difference in gradation characteristics between the target image area to be subjected to spatial processing and the surrounding image area of the target image area. Do the average. The visual processing means performs visual processing of the target image area based on the gradation characteristics of the target image area and the spatial processing signal.
Here, the image area means an area including a plurality of pixels in the image, or a pixel itself. The gradation characteristics are values based on pixel values such as brightness and brightness for each pixel. For example, the gradation characteristics of the image area include an average value (simple average or weighted average) of pixel values included in the image area, a maximum value, or a minimum value.

The spatial processing means performs spatial processing of the target image region using the gradation characteristics of the peripheral image region. In the spatial processing, the gradation characteristics of the target image area and the peripheral image area are weighted averaged. The weight in the weighted average is set based on a difference in gradation characteristics between the target image area and the peripheral image area.
In the visual processing device of the present invention, it is possible to suppress the influence of the spatially processed signal from image regions having greatly different gradation characteristics. For example, it is possible to derive an appropriate spatial processing signal even when the peripheral image region is an image including the boundary of an object and the gradation characteristics are significantly different from the target image region. As a result, even in visual processing using a spatial processing signal, it is possible to suppress the occurrence of pseudo contours. For this reason, it is possible to realize visual processing that improves the visual effect.
The visual processing device according to attachment 24 is the visual processing device according to attachment 23, in which the weighting decreases as the absolute value of the difference in gradation characteristics increases.

Here, the weight may be given as a value that monotonously decreases in accordance with the difference in gradation characteristics, or is set to a predetermined value by comparing the predetermined threshold value with the difference in gradation characteristics. It may be a thing.
In the visual processing device of the present invention, it is possible to suppress the influence of the spatially processed signal from image regions having greatly different gradation characteristics. For example, it is possible to derive an appropriate spatial processing signal even when the peripheral image region is an image including the boundary of an object and the gradation characteristics are significantly different from the target image region. As a result, even in visual processing using a spatial processing signal, it is possible to suppress the occurrence of pseudo contours. For this reason, it is possible to realize visual processing that improves the visual effect.
The visual processing device according to attachment 25 is the visual processing device according to attachment 23 or 24, in which the weighting decreases as the distance between the target image region and the peripheral image region increases.

Here, the weight may be given as a value that monotonously decreases in accordance with the distance between the target image area and the surrounding image area, or may be determined by comparing the predetermined threshold with the distance. It may be set to the value of.
In the visual processing device of the present invention, it is possible to suppress the influence of the spatially processed signal from the peripheral image region that is separated from the target image region. For this reason, if the peripheral image area is an image including the boundary of an object and the gradation characteristics are significantly different from the target image area, the peripheral image area is separated from the target image area. It is possible to suppress the influence from the region and derive a more appropriate spatial processing signal.
The visual processing device according to attachment 26 is the visual processing device according to any one of attachments 23 to 25, in which the image region is composed of a plurality of pixels. The gradation characteristics of the target image area and the peripheral image area are determined as feature values of pixel values constituting each image area.

In the visual processing device of the present invention, when performing spatial processing for each image region, not only the pixels included in each image region, but also the gradation characteristics of pixels included in a wide image region including peripheral image regions. To process. For this reason, it is possible to perform more appropriate spatial processing. As a result, even in visual processing using a spatial processing signal, it is possible to suppress the occurrence of pseudo contours. For this reason, it is possible to realize visual processing that improves the visual effect.
The visual processing device according to attachment 27 includes target image region determination means, peripheral image region determination means, gradation conversion characteristic derivation means, and gradation processing means. The target image area determining means determines a target image area from which the gradation conversion characteristics are derived from the input image signal. The peripheral image region determining means determines at least one peripheral image region including a plurality of pixels located around the target image region. The gradation conversion characteristic deriving means derives the gradation conversion characteristic of the target image area using the peripheral image data of the peripheral image area. The gradation processing means performs gradation processing of the image signal in the target image area based on the derived gradation conversion characteristics.

The target image region is, for example, a pixel included in the image signal, an image block obtained by dividing the image signal into predetermined units, or a region composed of a plurality of other pixels. The peripheral image area is, for example, an area constituted by an image block obtained by dividing an image signal into predetermined units and other plural pixels. The peripheral image data is image data of the peripheral image region or data derived from the image data. For example, the pixel value of the peripheral image region, gradation characteristics (brightness or brightness for each pixel), thumbnail (reduced image or Thinned image with reduced resolution). Further, the peripheral image area only needs to be positioned around the target image area, and does not need to be an area surrounding the target image area.
In the visual processing device of the present invention, when the gradation conversion characteristic of the target image area is determined, the determination is performed using the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing for each target image region, and it is possible to realize gradation processing that further improves the visual effect.

The visual processing method according to attachment 28 includes a target image region determination step, a peripheral image region determination step, a gradation conversion characteristic derivation step, and a gradation processing step. The target image region determination step determines a target image region from which the gradation conversion characteristics are derived from the input image signal. The peripheral image region determination step determines at least one peripheral image region including a plurality of pixels located around the target image region. In the gradation conversion characteristic deriving step, the gradation conversion characteristic of the target image area is derived using the peripheral image data of the peripheral image area. In the gradation processing step, gradation processing of the image signal in the target image area is performed based on the derived gradation conversion characteristics.
In the visual processing method of the present invention, when the gradation conversion characteristic of the target image area is determined, the determination is performed using the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing for each target image region, and it is possible to realize gradation processing that further improves the visual effect.

The visual processing program according to attachment 29 is a visual processing program for performing a visual processing method for performing visual processing of an input image signal using a computer. The visual processing method includes a target image region determination step, a peripheral image region determination step, a gradation conversion characteristic derivation step, and a gradation processing step. The target image region determination step determines a target image region from which the gradation conversion characteristics are derived from the input image signal. The peripheral image region determination step determines at least one peripheral image region including a plurality of pixels located around the target image region. In the gradation conversion characteristic deriving step, the gradation conversion characteristic of the target image area is derived using the peripheral image data of the peripheral image area. In the gradation processing step, gradation processing of the image signal in the target image area is performed based on the derived gradation conversion characteristics.
In the visual processing program of the present invention, when the gradation conversion characteristic of the target image area is determined, the determination is performed using the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing for each target image region, and it is possible to realize gradation processing that further improves the visual effect.

The semiconductor device according to attachment 30 includes a target image region determining unit, a peripheral image region determining unit, a gradation conversion characteristic deriving unit, and a gradation processing unit. The target image region determination unit determines a target image region from which the gradation conversion characteristics are derived from the input image signal. The peripheral image region determination unit determines at least one peripheral image region including a plurality of pixels located around the target image region. The gradation conversion characteristic deriving unit derives the gradation conversion characteristic of the target image area using the peripheral image data of the peripheral image area. The gradation processing unit performs gradation processing of the image signal in the target image area based on the derived gradation conversion characteristics.
In the semiconductor device of the present invention, when the gradation conversion characteristic of the target image area is determined, the determination is performed using the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing for each target image region, and it is possible to realize gradation processing that further improves the visual effect.

[Second note]
Furthermore, the present invention described in the above embodiment can also be expressed as follows.
<Content of second supplementary note>
(Appendix 201)
A visual processing device that performs gradation processing on an input image signal for each image region,
A gradation conversion characteristic of the target image area using peripheral image data of at least one peripheral image area that is located around the target image area to be subjected to the gradation processing and includes a plurality of pixels Gradation conversion characteristic deriving means for deriving
Gradation processing means for performing gradation processing of an image signal of the target image area based on the derived gradation conversion characteristics;
A visual processing device comprising:

(Appendix 202)
The peripheral image region is an image block obtained by dividing the image signal into predetermined units.
The visual processing device according to attachment 201.
(Appendix 203)
The gradation conversion characteristic deriving means derives the gradation conversion characteristic of the target image area by further using the target image data of the target image area.
The visual processing device according to attachment 201 or 202.
(Appendix 204)
The gradation conversion characteristic deriving unit derives a feature parameter that is a parameter indicating a feature of the target image region using the target image data and the peripheral image data, and is derived by the feature parameter deriving unit. Gradation conversion characteristic determination means for determining the gradation conversion characteristic based on the feature parameter of the target image area
The visual processing device according to attachment 203.

(Appendix 205)
The feature parameter is a histogram,
The visual processing device according to attachment 204.
(Appendix 206)
The gradation conversion characteristic determining means selects the gradation conversion characteristic tabulated in advance using the feature parameter,
The visual processing device according to attachment 204.
(Appendix 207)
The gradation conversion characteristics tabulated in advance can be changed.
The visual processing device according to attachment 206.

(Appendix 208)
The change of the gradation conversion characteristic is realized by correcting at least a part of the gradation conversion characteristic,
The visual processing device according to attachment 207.
(Appendix 209)
The gradation conversion characteristic determining means generates the gradation conversion characteristic by a predetermined operation using the feature parameter;
The visual processing device according to attachment 204.
(Appendix 210)
The predetermined calculation can be changed,
The visual processing device according to attachment 209.

(Appendix 211)
The change of the calculation is realized by correcting at least a part of the calculation,
The visual processing device according to attachment 210.
(Appendix 212)
The gradation conversion characteristic is obtained by interpolating or extrapolating a plurality of the gradation conversion characteristics,
The visual processing device according to attachment 204.
(Appendix 213)
A visual processing method for gradation-processing an input image signal for each image area,
The gradation conversion of the target image region using peripheral image data of at least one peripheral image region that is located around the target image region to be subjected to the gradation processing and includes a plurality of pixels Gradation conversion characteristic deriving step for deriving characteristics;
A gradation processing step for performing gradation processing of an image signal of the target image area based on the derived gradation conversion characteristics;
A visual processing method comprising:

(Appendix 214)
The peripheral image region is an image block obtained by dividing the image signal into predetermined units.
The visual processing method according to attachment 213.
(Appendix 215)
The gradation conversion characteristic deriving step derives the gradation conversion characteristic of the target image area by further using target image data of the target image area.
The visual processing method according to attachment 213 or 214.
(Appendix 216)
In the gradation conversion characteristic deriving step, a characteristic parameter deriving step for deriving a characteristic parameter that is a parameter indicating a characteristic of the target image region using the target image data and the peripheral image data, and deriving in the characteristic parameter deriving step A gradation conversion characteristic determination step for determining the gradation conversion characteristic based on the feature parameter of the target image area
The visual processing method according to attachment 215.

(Appendix 217)
A visual processing program for performing a visual processing method for performing gradation processing on an input image signal for each image region using a computer,
The visual processing method includes:
The gradation conversion of the target image region using peripheral image data of at least one peripheral image region that is located around the target image region to be subjected to the gradation processing and includes a plurality of pixels Gradation conversion characteristic deriving step for deriving characteristics;
A gradation processing step for performing gradation processing of an image signal of the target image area based on the derived gradation conversion characteristics;
A visual processing method comprising:
Visual processing program.

(Appendix 218)
The peripheral image region is an image block obtained by dividing the image signal into predetermined units.
The visual processing program according to attachment 217.
(Appendix 219)
The gradation conversion characteristic deriving step derives the gradation conversion characteristic of the target image area by further using target image data of the target image area.
The visual processing program according to attachment 217 or 218.
(Appendix 220)
In the gradation conversion characteristic deriving step, a characteristic parameter deriving step for deriving a characteristic parameter that is a parameter indicating a characteristic of the target image region using the target image data and the peripheral image data, and deriving in the characteristic parameter deriving step A gradation conversion characteristic determination step for determining the gradation conversion characteristic based on the feature parameter of the target image area
The visual processing program according to attachment 219.

(Appendix 221)
A semiconductor device that performs gradation processing on an input image signal for each image region,
The gradation conversion of the target image region using peripheral image data of at least one peripheral image region that is located around the target image region to be subjected to the gradation processing and includes a plurality of pixels A gradation conversion characteristic deriving unit for deriving the characteristic;
A gradation processing unit that performs gradation processing of an image signal of the target image area based on the derived gradation conversion characteristics;
A semiconductor device comprising:
(Appendix 222)
The peripheral image region is an image block obtained by dividing the image signal into predetermined units.
The semiconductor device according to appendix 221.

(Appendix 223)
The gradation conversion characteristic deriving unit derives the gradation conversion characteristic of the target image area by further using the target image data of the target image area;
The semiconductor device according to appendix 221 or 222.
(Appendix 224)
The gradation conversion characteristic deriving unit derives a feature parameter that is a parameter indicating a feature of the target image region using the target image data and the peripheral image data, and is derived by the feature parameter deriving unit. A gradation conversion characteristic determination unit that determines the gradation conversion characteristic based on the feature parameter of the target image area
The semiconductor device according to appendix 223.

<Explanation of second supplementary note>
The visual processing device according to attachment 201 is a visual processing device that performs gradation processing on an input image signal for each image region, and includes gradation conversion characteristic deriving means and gradation processing means. The gradation conversion characteristic deriving means is an image area located around the target image area to be subjected to gradation processing, and uses the peripheral image data of at least one peripheral image area including a plurality of pixels, The gradation conversion characteristics of the area are derived. The gradation processing means performs gradation processing of the image signal in the target image area based on the derived gradation conversion characteristics.
The target image region is, for example, a pixel included in the image signal, an image block obtained by dividing the image signal into predetermined units, or a region composed of a plurality of other pixels. The peripheral image area is, for example, an area constituted by an image block obtained by dividing an image signal into predetermined units and other plural pixels. The peripheral image data is image data of the peripheral image region or data derived from the image data. For example, the pixel value of the peripheral image region, gradation characteristics (brightness or brightness for each pixel), thumbnail (reduced image or Thinned image with reduced resolution). Further, the peripheral image area only needs to be positioned around the target image area, and does not need to be an area surrounding the target image area.

In the visual processing device of the present invention, when the gradation conversion characteristic of the target image area is determined, the determination is performed using the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing for each target image region, and it is possible to realize gradation processing that further improves the visual effect.
The visual processing device according to attachment 202 is the visual processing device according to attachment 201, in which the peripheral image region is an image block obtained by dividing an image signal into predetermined units.
Here, the image block is an area obtained by dividing the image signal into rectangles.
In the visual processing device according to the present invention, it is possible to process the peripheral image area in units of image blocks. For this reason, it is possible to reduce the processing load required to determine the peripheral image region and to derive the gradation conversion characteristics.

The visual processing device according to attachment 203 is the visual processing device according to attachment 201 or 202, wherein the gradation conversion characteristic deriving means further uses the target image data of the target image region to Derivation of conversion characteristics.
The target image data is image data of the target image region or data derived from the image data. For example, the pixel value of the target image region, gradation characteristics (brightness or brightness for each pixel), thumbnail (reduced image or Thinned image with reduced resolution).
In the visual processing device of the present invention, when determining the gradation conversion characteristics of the target image area, the determination is performed using not only the target image data of the target image area but also the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing of the target image region, and it is possible to realize gradation processing that further improves the visual effect.

The visual processing device according to attachment 204 is the visual processing device according to attachment 203, in which the gradation conversion characteristic deriving means is a parameter indicating the characteristics of the target image region using the target image data and the peripheral image data. Feature parameter deriving means for deriving feature parameters, and tone conversion characteristic determining means for determining tone conversion characteristics based on the feature parameters of the target image area derived by the feature parameter deriving means.
The characteristic parameter is, for example, an average value (simple average value, weighted average value, etc.) of target image data and peripheral image data, a representative value (maximum value, minimum value, median value, etc.), a histogram, or the like. Here, the histogram is a distribution of gradation characteristics of the target image data and the peripheral image data, for example.
In the visual processing device of the present invention, feature parameters are derived using not only target image data but also peripheral image data. For this reason, it is possible to add a spatial processing effect to the gradation processing of the target image region, and it is possible to realize gradation processing that further improves the visual effect. As a more specific effect, it is possible to suppress the occurrence of a pseudo contour due to gradation processing. In addition, it is possible to prevent the boundary of the target image area from being unnaturally conspicuous.

The visual processing device according to attachment 205 is the visual processing device according to attachment 204, wherein the characteristic parameter is a histogram.
The gradation conversion characteristic determining means determines, for example, a cumulative curve obtained by accumulating histogram values as the gradation conversion characteristic, or selects a gradation conversion characteristic corresponding to the histogram.
In the visual processing device of the present invention, a histogram is created using not only target image data but also peripheral image data. For this reason, it is possible to suppress the occurrence of a pseudo contour due to gradation processing. In addition, it is possible to prevent the boundary of the target image area from being unnaturally conspicuous.
The visual processing device according to attachment 206 is the visual processing device according to attachment 204, wherein the gradation conversion characteristic determining means selects the gradation conversion characteristics tabulated in advance using the characteristic parameter. And

Here, the gradation conversion characteristics are tabulated data, and the characteristics of the target image data after gradation processing on the target image data are stored in the table.
The gradation conversion characteristic determining means selects a table corresponding to each of the characteristic parameter values.
In the visual processing device of the present invention, gradation processing is performed using the tabulated gradation conversion characteristics. For this reason, it is possible to speed up the gradation processing. In addition, since one table is selected from a plurality of tables and gradation processing is performed, appropriate gradation processing can be performed.
The visual processing device according to attachment 207 is the visual processing device according to attachment 206, wherein the gradation conversion characteristics tabulated in advance can be changed.
In the visual processing device of the present invention, by changing the tone conversion characteristics, the tone processing characteristics can be variously changed without changing the hardware configuration.

The visual processing device according to attachment 208 is the visual processing device according to attachment 207, wherein the change of the gradation conversion characteristic is realized by correcting at least a part of the gradation conversion characteristic. To do.
In the visual processing device of the present invention, the gradation conversion characteristic is changed by correcting at least a part of the gradation conversion characteristic. For this reason, various gradation processes can be realized while reducing the storage capacity for the gradation conversion characteristics.
The visual processing device according to attachment 209 is the visual processing device according to attachment 204, wherein the gradation conversion characteristic determining means generates the gradation conversion characteristic by a predetermined operation using the characteristic parameter. Features.
Here, the gradation conversion characteristic gives the target image data after gradation processing on the target image data. In addition, the calculation for generating the gradation conversion characteristic is determined in advance using the feature parameter. More specifically, for example, an operation corresponding to each feature parameter value is selected, or an operation is generated according to the feature parameter value.

In the visual processing device of the present invention, it is not necessary to store gradation conversion characteristics in advance, and the storage capacity for storing gradation conversion characteristics can be reduced.
The visual processing device according to attachment 210 is the visual processing device according to attachment 209, wherein a predetermined calculation can be changed.
In the visual processing device of the present invention, it is possible to change the characteristics of gradation processing in various ways by changing the calculation.
The visual processing device according to attachment 211 is the visual processing device according to attachment 210, characterized in that the change of the calculation is realized by correcting at least a part of the calculation.
In the visual processing device of the present invention, the gradation conversion characteristic is changed by correcting at least a part of the calculation. For this reason, even if the storage capacities for storing the calculations are the same, it is possible to realize more various gradation processes.

The visual processing device according to attachment 212 is the visual processing device according to attachment 204, wherein the gradation conversion characteristics are obtained by interpolating or extrapolating a plurality of gradation conversion characteristics. To do.
Here, the gradation conversion characteristics are, for example, characteristics of target image data after gradation processing on the target image data. The gradation conversion characteristics are given in, for example, a table format or a calculation format.
In the visual processing device of the present invention, it is possible to perform gradation processing using a new gradation conversion characteristic obtained by interpolating or extrapolating a plurality of gradation conversion characteristics. For this reason, even if the storage capacity for storing the gradation conversion characteristics is reduced, more various gradation processes can be realized.

The visual processing method according to attachment 213 is a visual processing method for performing gradation processing on an input image signal for each image area, and includes a gradation conversion characteristic deriving step and a gradation processing step. The gradation conversion characteristic deriving step is an image area located around the target image area to be subjected to gradation processing, and uses the peripheral image data of at least one peripheral image area including a plurality of pixels, The gradation conversion characteristics of the area are derived. In the gradation processing step, gradation processing of the image signal in the target image area is performed based on the derived gradation conversion characteristics.
In the visual processing method of the present invention, when the gradation conversion characteristic of the target image area is determined, the determination is performed using the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing for each target image region, and it is possible to realize gradation processing that further improves the visual effect.

The visual processing method according to attachment 214 is the visual processing method according to attachment 213, in which the peripheral image region is an image block obtained by dividing the image signal into predetermined units.
In the visual processing method of the present invention, it is possible to process the peripheral image area in units of image blocks. For this reason, it is possible to reduce the processing load required to determine the peripheral image region and to derive the gradation conversion characteristics.
The visual processing method according to attachment 215 is the visual processing method according to attachment 213 or 214, in which the gradation conversion characteristic deriving step further uses the target image data of the target image area to perform gradation of the target image area. Derivation of conversion characteristics.
In the visual processing method of the present invention, when determining the gradation conversion characteristics of the target image area, the determination is performed using not only the target image data of the target image area but also the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing of the target image region, and it is possible to realize gradation processing that further improves the visual effect.

The visual processing method according to attachment 216 is the visual processing method according to attachment 215, and the gradation conversion characteristic deriving step is a parameter indicating the characteristics of the target image region using the target image data and the peripheral image data. A feature parameter deriving step for deriving the feature parameter; and a tone conversion property determining step for determining the tone conversion property based on the feature parameter of the target image region derived in the feature parameter deriving step.
In the visual processing method of the present invention, feature parameters are derived using not only target image data but also peripheral image data. For this reason, it is possible to add a spatial processing effect to the gradation processing of the target image region, and it is possible to realize gradation processing that further improves the visual effect. As a more specific effect, it is possible to suppress the occurrence of a pseudo contour due to gradation processing. In addition, it is possible to prevent the boundary of the target image area from being noticeable unnaturally.

The visual processing program described in appendix 217 is a visual processing program for performing a visual processing method for performing gradation processing on an input image signal for each image region using a computer. The visual processing method includes a gradation conversion characteristic deriving step and a gradation processing step. The gradation conversion characteristic deriving step is an image area located around the target image area to be subjected to gradation processing, and uses the peripheral image data of at least one peripheral image area including a plurality of pixels, The gradation conversion characteristics of the area are derived. In the gradation processing step, gradation processing of the image signal in the target image area is performed based on the derived gradation conversion characteristics.
In the visual processing program of the present invention, when the gradation conversion characteristic of the target image area is determined, the determination is performed using the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing for each target image region, and it is possible to realize gradation processing that further improves the visual effect.

The visual processing program described in appendix 218 is the visual processing program described in appendix 217, and the peripheral image area is an image block obtained by dividing an image signal into predetermined units.
In the visual processing program of the present invention, it is possible to process the peripheral image area in units of image blocks. For this reason, it is possible to reduce the processing load required to determine the peripheral image region and to derive the gradation conversion characteristics.
The visual processing program according to attachment 219 is the visual processing program according to attachment 217 or 218, wherein the gradation conversion characteristic deriving step further uses the target image data of the target image area to Derivation of conversion characteristics.
In the visual processing program of the present invention, when determining the gradation conversion characteristics of the target image area, the determination is performed using not only the target image data of the target image area but also the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing of the target image region, and it is possible to realize gradation processing that further improves the visual effect.

The visual processing program described in appendix 220 is the visual processing program described in appendix 219, and the gradation conversion characteristic deriving step is a parameter indicating the characteristics of the target image region using the target image data and the peripheral image data. A characteristic parameter deriving step for deriving the characteristic parameter; and a gradation conversion characteristic determining step for determining the gradation conversion characteristic based on the characteristic parameter of the target image region derived in the characteristic parameter deriving step.
In the visual processing program of the present invention, feature parameters are derived using not only target image data but also peripheral image data. For this reason, it is possible to add a spatial processing effect to the gradation processing of the target image region, and it is possible to realize gradation processing that further improves the visual effect. As a more specific effect, it is possible to suppress the occurrence of a pseudo contour due to gradation processing. In addition, it is possible to prevent the boundary of the target image area from being unnaturally conspicuous.

The semiconductor device described in appendix 221 is a semiconductor device that performs gradation processing on an input image signal for each image region, and includes a gradation conversion characteristic deriving unit and a gradation processing unit. The gradation conversion characteristic deriving unit is an image area located in the periphery of the target image area to be subjected to gradation processing, and uses the peripheral image data of at least one peripheral image area including a plurality of pixels. The gradation conversion characteristics of the area are derived. The gradation processing unit performs gradation processing of the image signal in the target image area based on the derived gradation conversion characteristics.
In the semiconductor device of the present invention, when the gradation conversion characteristic of the target image area is determined, the determination is performed using the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing for each target image region, and it is possible to realize gradation processing that further improves the visual effect.

The semiconductor device described in appendix 222 is the semiconductor device described in appendix 221, and the peripheral image region is an image block obtained by dividing an image signal into predetermined units.
In the semiconductor device of the present invention, it is possible to process the peripheral image area in units of image blocks. For this reason, it is possible to reduce the processing load required to determine the peripheral image region and to derive the gradation conversion characteristics.
The semiconductor device described in appendix 223 is the semiconductor device described in appendix 221 or 222, wherein the gradation conversion characteristic deriving unit further uses the target image data of the target image area to perform gradation conversion characteristics of the target image area. Is derived.
In the semiconductor device of the present invention, when determining the gradation conversion characteristics of the target image area, the determination is performed using not only the target image data of the target image area but also the peripheral image data of the peripheral image area. For this reason, it is possible to add a spatial processing effect to the gradation processing of the target image region, and it is possible to realize gradation processing that further improves the visual effect.

The semiconductor device described in appendix 224 is the semiconductor device described in appendix 223, wherein the gradation conversion characteristic deriving unit is a feature parameter that is a parameter indicating the feature of the target image region using the target image data and the peripheral image data. And a tone conversion characteristic determining unit that determines the tone conversion characteristic based on the feature parameter of the target image area derived by the feature parameter deriving unit.
In the semiconductor device of the present invention, feature parameters are derived using not only target image data but also peripheral image data. For this reason, it is possible to add a spatial processing effect to the gradation processing of the target image region, and it is possible to realize gradation processing that further improves the visual effect. As a more specific effect, it is possible to suppress the occurrence of a pseudo contour due to gradation processing. In addition, it is possible to prevent the boundary of the target image area from being unnaturally conspicuous.

  The visual processing device according to the present invention can also be applied to uses such as a visual processing device that performs gradation processing of an image signal that needs to realize gradation processing that further improves the visual effect.

Block diagram for explaining the structure of the visual processing device 1 (first embodiment) Explanatory drawing explaining image area Pm (1st Embodiment). Explanatory drawing explaining the brightness histogram Hm (1st Embodiment). Explanatory drawing explaining the gradation conversion curve Cm (first embodiment) Flowchart for explaining visual processing method (first embodiment) Block diagram for explaining the structure of the visual processing device 11 (second embodiment) Explanatory drawing explaining gradation conversion curve candidate G1-Gp (2nd Embodiment). Explanatory drawing explaining 2D LUT41 (2nd Embodiment). Explanatory drawing explaining operation | movement of the gradation correction | amendment part 15 (2nd Embodiment). Flowchart explaining visual processing method (second embodiment) Explanatory drawing explaining the modification of selection of the gradation conversion curve Cm (2nd Embodiment). Explanatory drawing explaining the gradation process as a modification (2nd Embodiment) Block diagram for explaining the structure of the gradation processing execution unit 44 (second embodiment) Explanatory drawing explaining the relationship between curve parameter P1 and P2 and gradation conversion curve candidate G1-Gp (2nd Embodiment). Explanatory drawing explaining the relationship between curve parameter P1 and P2 and the selection signal Sm (2nd Embodiment). Explanatory drawing explaining the relationship between curve parameter P1 and P2 and the selection signal Sm (2nd Embodiment). Explanatory drawing explaining the relationship between curve parameter P1 and P2 and gradation conversion curve candidate G1-Gp (2nd Embodiment). Explanatory drawing explaining the relationship between curve parameter P1 and P2 and the selection signal Sm (2nd Embodiment). Block diagram for explaining the structure of the visual processing device 21 (third embodiment) Explanatory drawing explaining operation | movement of the selection signal correction | amendment part 24 (3rd Embodiment). Flowchart explaining visual processing method (third embodiment) Block diagram for explaining the structure of the visual processing device 61 (fourth embodiment) Explanatory drawing explaining the spatial processing of the spatial processing part 62 (4th Embodiment). Table for explaining weighting factor [Wij] (fourth embodiment) Explanatory drawing explaining the effect of the visual processing by the visual processing device 61 (4th Embodiment). Block diagram for explaining the structure of the visual processing device 961 (fourth embodiment) Explanatory drawing explaining the spatial processing of the spatial processing part 962 (4th Embodiment). Table for explaining weighting factor [Wij] (fourth embodiment) Block diagram for explaining the overall configuration of the content supply system (sixth embodiment) Example of mobile phone equipped with visual processing device of the present invention (sixth embodiment) Block diagram for explaining the configuration of a mobile phone (sixth embodiment) Example of digital broadcasting system (sixth embodiment) Block diagram for explaining the structure of the visual processing device 300 (background art) Explanatory drawing explaining image area Sm (background art) Explanatory drawing explaining brightness histogram Hm (background art) Explanatory drawing explaining the gradation conversion curve Cm (background art)

Explanation of symbols

1,11,21,61 Visual processing device 2,12,22 Image segmentation unit 3 Histogram creation unit 4 Tone curve creation unit 5, 20, 30 Tone processing unit 10 Tone conversion curve derivation unit 13, 23 Selection signal derivation Units 14, 25 gradation processing execution unit 15 gradation correction unit 24 selection signal correction unit IS input signal OS output signal Pm image area Em wide area image area Hm brightness histogram Cm gradation conversion curve Sm selection signal SS selection signal CS for each pixel Gradation processing signal

Claims (9)

An image dividing unit for dividing the input image into a plurality of image regions;
For each image area, determine a wide area image area composed of a plurality of image areas around the image area ,
An area conversion characteristic deriving unit for deriving an area gradation conversion characteristic for the image area according to the feature amount of the wide area image area;
The pixel value of the conversion target pixel included in the input image, the region gradation conversion characteristic for the target image region that is the image region including the conversion target pixel, and the region gradation for the adjacent image region adjacent to the target image region A gradation processing unit that obtains a conversion pixel value of the conversion target pixel according to conversion characteristics and a position coordinate of the conversion target pixel;
Characterized by comprising,
Gradation conversion processing device. The gradation processing unit
The area gradation conversion characteristics for the target image area and the area gradation conversion characteristics for the adjacent image area,
The pixel value is converted by a gradation conversion characteristic corrected according to the position coordinates,
The gradation conversion processing apparatus according to claim 1. An image dividing unit for dividing the input image into a plurality of image regions;
For each image area, determine a wide area image area composed of a plurality of image areas around the image area ,
An area conversion characteristic deriving unit for deriving an area gradation conversion characteristic for the image area according to the feature amount of the wide area image area;
The pixel value of the conversion target pixel included in the input image, the region gradation conversion characteristic for the target image region that is the image region including the conversion target pixel, and the region gradation for the adjacent image region adjacent to the target image region A gradation processing unit that obtains a conversion pixel value of the conversion target pixel according to conversion characteristics and a position coordinate of the conversion target pixel;
A display unit for displaying the processed signal after gradation processing;
Characterized by comprising,
Image display device. A receiver for receiving a video signal;
A decoding unit for decoding the video signal and outputting an image signal;
An image dividing unit for dividing the image signal into a plurality of image regions;
For each image area, determine a wide area image area composed of a plurality of image areas around the image area ,
An area conversion characteristic deriving unit for deriving an area gradation conversion characteristic for the image area according to the feature amount of the wide area image area;
The pixel value of the conversion target pixel included in the input image, the region gradation conversion characteristic for the target image region that is the image region including the conversion target pixel, and the region gradation for the adjacent image region adjacent to the target image region A gradation processing unit that obtains a conversion pixel value of the conversion target pixel according to conversion characteristics and a position coordinate of the conversion target pixel;
A display unit for displaying the processed signal after gradation processing;
Characterized by comprising,
television. A receiver for receiving a video signal;
A decoding unit for decoding the video signal and outputting an image signal;
An image dividing unit for dividing the image signal into a plurality of image regions;
For each image area, determine a wide area image area composed of a plurality of image areas around the image area ,
An area conversion characteristic deriving unit for deriving an area gradation conversion characteristic for the image area according to the feature amount of the wide area image area;
The pixel value of the conversion target pixel included in the input image, the region gradation conversion characteristic for the target image region that is the image region including the conversion target pixel, and the region gradation for the adjacent image region adjacent to the target image region A gradation processing unit that obtains a conversion pixel value of the conversion target pixel according to conversion characteristics and a position coordinate of the conversion target pixel;
A display unit for displaying the processed signal after gradation processing;
Characterized by comprising,
Mobile information terminal. A shooting unit for shooting an image and generating an image signal;
An image dividing unit for dividing the image signal into a plurality of image regions;
For each image area, determine a wide area image area composed of a plurality of image areas around the image area ,
An area conversion characteristic deriving unit for deriving an area gradation conversion characteristic for the image area according to the feature amount of the wide area image area;
The pixel value of the conversion target pixel included in the input image, the region gradation conversion characteristic for the target image region that is the image region including the conversion target pixel, and the region gradation for the adjacent image region adjacent to the target image region A gradation processing unit that obtains a conversion pixel value of the conversion target pixel according to conversion characteristics and a position coordinate of the conversion target pixel;
A camera, comprising: An image dividing step for dividing the input image into a plurality of image regions;
For each image area, determine a wide area image area composed of a plurality of image areas around the image area ,
An area conversion characteristic deriving step for deriving an area gradation conversion characteristic for the image area according to the feature amount of the wide area image area;
The pixel value of the conversion target pixel included in the input image, the region gradation conversion characteristic for the target image region that is the image region including the conversion target pixel, and the region gradation for the adjacent image region adjacent to the target image region A gradation processing step for obtaining a conversion pixel value of the conversion target pixel according to the conversion characteristics and the position coordinates of the conversion target pixel;
Including,
Gradation conversion processing method. An integrated circuit used in a gradation conversion processing device,
An image dividing step for dividing the input image into a plurality of image regions;
For each image area, determine a wide area image area composed of a plurality of image areas around the image area ,
An area conversion characteristic deriving step for deriving an area gradation conversion characteristic for the image area according to the feature amount of the wide area image area;
The pixel value of the conversion target pixel included in the input image, the region gradation conversion characteristic for the target image region that is the image region including the conversion target pixel, and the region gradation for the adjacent image region adjacent to the target image region A gradation processing step for obtaining a conversion pixel value of the conversion target pixel according to the conversion characteristics and the position coordinates of the conversion target pixel;
Run the
It is used for a gradation conversion processing device,
Integrated circuit. An image processing program for performing gradation conversion processing by a computer,
The image processing program includes:
An image dividing step for dividing the input image into a plurality of image regions;
For each image area, determine a wide area image area composed of a plurality of image areas around the image area ,
An area conversion characteristic deriving step for deriving an area gradation conversion characteristic for the image area according to the feature amount of the wide area image area;
The pixel value of the conversion target pixel included in the input image, the region gradation conversion characteristic for the target image region that is the image region including the conversion target pixel, and the region gradation for the adjacent image region adjacent to the target image region A gradation processing step for obtaining a conversion pixel value of the conversion target pixel according to the conversion characteristics and the position coordinates of the conversion target pixel;
A gradation conversion processing method, comprising:
Is characterized by having the computer perform
Image processing program.

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