JP5476897B2 - Image processing apparatus, image output apparatus, and image processing method - Google Patents

Description

  The present invention relates to an image processing device, an image output device, an image processing method, and the like.

  Image display devices and image printing devices as image output devices are limited in the range of colors that can be output. For this reason, the image output apparatus cannot reproduce all colors that can be recognized by the human eye. The color gamut, which is the color range, varies depending on the type of the image output device, and images of various color gamuts such as sRGB (standard RGB) and Adobe RGB can be input to the image output device. Therefore, the color gamut of the input image may be different from the color gamut of the image output device. When the color gamut of the image output device is narrower than the color gamut of the input image, a process called color compression is performed. It is done to compress the colors.

  This color compression processing is disclosed in Patent Document 1, for example. This patent document 1 compares the color gamut of an input image with the color gamut of an image output device, and performs color compression for a hue whose input image has a larger color gamut than the color gamut of the image output device. An image processing method is described in which a hue whose input image has a smaller color gamut than the color gamut is subjected to color expansion opposite to color compression. In this image processing method, when the input image is divided into a plurality of regions, the above-described processing is performed for each region, and the compression rate at the time of color compression and the expansion rate at the time of color expansion become higher in the high saturation region. Is processed as follows.

JP 2000-83177 A

  However, with the technique disclosed in Patent Document 1, the higher the saturation region, the higher the compression rate during color compression and the expansion rate during color expansion. For this reason, as in a general color compression process, there is a problem that, in a high saturation area, the color change becomes small during color compression, and the details of the image are crushed.

  The present invention has been made in view of the above technical problems. According to some aspects of the present invention, it is possible to provide an image processing device, an image output device, an image processing method, and the like that improve the appearance of image details when color compression is performed.

  (1) According to one aspect of the present invention, an image processing device that corrects image data supplied to an image output device uses the image data based on a color gamut of an input image and a color gamut of the image output device. A color compression unit that compresses the saturation component of the image data at a compression rate corresponding to the combination of the brightness component and the hue component of the image data, and the saturation component of the image data for the image data in a given spatial frequency band A correction amount calculation unit that calculates the correction amount according to the compression rate, and a correction unit that corrects the saturation component of the image data compressed by the color compression unit using the correction amount.

  In this aspect, the saturation component of the image data is compressed at a compression rate corresponding to the combination of the lightness component and the hue component of the image data based on the color gamut of the input image and the color gamut of the image output device. At this time, for the image data in a given spatial frequency band, the saturation component of the image data is corrected in accordance with the compression ratio at the time of the above compression processing, so that it is lost due to the compression of the saturation component. By correcting the cracked portion, it is possible to improve the appearance of the detail portion of the image that is lost on the high saturation side during color compression.

  (2) The image processing apparatus according to another aspect of the present invention provides the image processing device according to a combination of a lightness component and a hue component of the image data based on a color gamut of the input image and a color gamut of the image output device. A compression rate calculation unit that calculates a compression rate of the saturation component of the image data, and the color compression unit compresses the saturation component of the image data at the compression rate calculated by the compression rate calculation unit.

  According to this aspect, since the compression rate is calculated based on the color gamut of the input image and the color gamut of the image output device, in addition to the above effects, the saturation component of the input image data is Therefore, the optimum correction can be performed, and it is possible to contribute to high image quality of the image after color compression.

  (3) In the image processing apparatus according to another aspect of the present invention, the compression rate calculation unit includes a saturation correction curve indicating a relationship between a saturation component Cin before color compression and a saturation component Cout after color compression. As the compression ratio, the inverse of the slope ΔCin / ΔCout in the saturation component Cin is calculated.

  According to this aspect, the compression ratio in the color compression processing performed according to the saturation correction curve can be faithfully reflected in the actual color compression processing, so that the saturation component after color compression is corrected with high accuracy. Will be able to.

  (4) In the image processing apparatus according to another aspect of the present invention, the compression rate calculation unit includes a saturation correction curve indicating a relationship between a saturation component Cin before color compression and a saturation component Cout after color compression. Cin / Cout is calculated as the compression rate.

  According to this aspect, since the compression rate in the color compression processing performed according to the saturation correction curve can be easily obtained, the saturation component after color compression is easily corrected while maintaining a certain degree of accuracy. Will be able to.

  (5) An image processing apparatus according to another aspect of the present invention includes a saturation noise removal unit that removes a given saturation noise component from the saturation component, and the correction unit uses the correction amount. The saturation component of the image data from which the saturation noise component has been removed by the saturation noise removal unit is corrected.

  According to this aspect, since the saturation component from which the saturation noise has been removed is corrected using the correction amount, in addition to the above effect, the image signal for distinguishing between the detail and the saturation noise can be obtained. Correction can be performed with high accuracy.

  (6) In the image processing apparatus according to another aspect of the present invention, the correction amount calculation unit increases the saturation component as the amount of the saturation noise component removed by the saturation noise removal unit decreases. The correction amount is calculated so as to increase the amount.

  According to this aspect, in addition to the above effect, it is possible to avoid a situation where the saturation noise is amplified and to surely improve the appearance of the detail portion of the image by color compression.

  (7) In the image processing device according to another aspect of the present invention, the correction amount calculation unit calculates the correction amount of the saturation component so that the amplification amount of the saturation component increases as the compression rate increases. To do.

  According to this aspect, in addition to the above effect, it is possible to reliably improve the appearance of the detail portion of the image lost due to the color compression.

  (8) In the image processing device according to another aspect of the present invention, the correction amount calculation unit performs the correction so that the amount of amplification of the saturation component in the high frequency region is larger than that in the low frequency region in the spatial frequency band. Calculate the amount.

  According to this aspect, in addition to the above-described effect, it is possible to reliably improve the appearance of the detail portion of the image lost by color compression without amplifying the saturation noise.

  (9) In another aspect of the present invention, an image output device that outputs an image based on image data is an image based on any of the image processing devices described above and the image data corrected by the image processing device. And an image output unit for outputting.

  According to this aspect, it is possible to provide an image output apparatus to which an image processing apparatus that improves the appearance of image details when color compression is performed.

  (10) According to another aspect of the present invention, there is provided an image processing method for correcting image data supplied to an image output device based on a color gamut of an input image and a color gamut of the image output device. A color compression step for compressing the saturation component of the image data at a compression rate corresponding to a combination of the lightness component and the hue component of the data, and the saturation of the image data for the image data in a given spatial frequency band A saturation component correction amount calculating step for calculating a component correction amount according to the compression ratio; and a saturation for correcting the saturation component of the image data compressed in the color compression step using the correction amount. Component correction step.

  In this aspect, the saturation component of the image data is compressed at a compression rate corresponding to the combination of the lightness component and the hue component of the image data based on the color gamut of the input image and the color gamut of the image output device. At this time, for the image data in a given spatial frequency band, the saturation component of the image data is corrected in accordance with the compression ratio at the time of the above compression processing, so that it is lost due to the compression of the saturation component. By correcting the cracked portion, it is possible to improve the appearance of the detail portion of the image that is lost on the high saturation side during color compression.

1 is a block diagram of a configuration example of an image display system according to an embodiment of the present invention. Explanatory drawing of the correction process performed in the image process part of FIG. The block diagram of the hardware structural example of the image process part of FIG. 4A and 4B are operation explanatory diagrams of the compression rate calculation circuit of FIG. FIG. 3 is an operation explanatory diagram of a color compression circuit. FIG. 4 is a block diagram of a configuration example of a detail emphasis circuit in FIG. 3. The block diagram of the structural example of the noise extraction and removal circuit of FIG. The figure which shows an example of the filter characteristic of the HPF circuit of FIG. 7, and an LPF circuit. The operation explanatory view of a weighting calculation circuit. Explanatory drawing of the weighting coefficient which the weighting calculation circuit demonstrated in FIG. 9 outputs. The block diagram of the structural example of the multistage filter circuit of FIG. FIG. 7 is a block diagram of a configuration example of a correction amount calculation circuit in FIG. 6. FIG. 13 is an operation explanatory diagram of the weight calculation circuit of FIG. 12. FIG. 13 is an operation explanatory diagram of the saturation gain calculation circuit of FIG. 12. Explanatory drawing of the effect of the detail emphasis process of the image process part in this embodiment. The flowchart of the example of a process of the image process part in this embodiment. FIG. 17 is a flowchart of a processing example of detail enhancement processing of FIG. 16 of the image processing unit in the present embodiment. The figure of the structural example of the projection part of FIG. 1 or FIG. The block diagram of the structural example of the correction amount calculation circuit in the 1st modification of this embodiment. 20A, 20B, and 20C are explanatory diagrams of operations of the first to third LUTs of FIG. The block diagram of the structural example of the correction amount calculation circuit in the 2nd modification of this embodiment. FIG. 22 is an operation explanatory diagram of the LUT in FIG. 21. Explanatory drawing of the compression rate in the 3rd modification of this embodiment. Explanatory drawing of the 3rd modification of this embodiment. FIG. 10 is a block diagram of a configuration example of a printer according to a fourth modification of the embodiment.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. The embodiments described below do not unduly limit the contents of the present invention described in the claims. In addition, all of the configurations described below are not necessarily indispensable configuration requirements for solving the problems of the present invention.

  In the following embodiments, an image display apparatus is described as an example of the image output apparatus according to the present invention. However, the image output apparatus according to the present invention is not limited to the image display apparatus. Similarly, an image display system will be described as an example of an image output system to which the image output apparatus according to the present invention is applied. However, the image output system to which the image output apparatus according to the present invention is applied is limited to the image display system. It is not a thing. Moreover, although the projector which is an image projection apparatus is demonstrated to an example as this image display apparatus, the image display apparatus which concerns on this invention is not limited to a projector.

1. Image Display System FIG. 1 is a block diagram showing a configuration example of an image display system according to an embodiment of the present invention.

  The image display system (image output system in a broad sense) 10 includes a projector (image output device in a broad sense) 20 that is an image display device, and a screen SCR. The projector 20 modulates light from a light source (not shown) based on the input image data, and displays the image by projecting the modulated light onto the screen SCR. Here, the color gamut of the input image represented by the input image data is partially wider than the color gamut of the projector 20 (projection unit 100), and the projector 20 performs color compression on the input image data, An image is displayed based on the image data after color compression.

  The projector 20 includes an image processing unit 30 (an image processing device in a broad sense) and a projection unit 100 (an image output unit in a broad sense). The image processing unit 30 corrects the input image data so that the details of the low saturation portion and the high saturation portion of the display image can be expressed without affecting the saturation region that is not the correction target, and projects the corrected image data. Output to the unit 100. The projection unit 100 projects light modulated based on the image data from the image processing unit 30 onto the screen SCR. At this time, the image processing unit 30 corrects the image data according to the compression rate so that the detail is enhanced even when color compression is performed based on the color gamut of the input image data and the color gamut of the projection unit 100. To do.

  1 shows an example in which the image processing unit 30 is provided inside the projector 20, but the image processing unit 30 may be provided outside the projector 20 or inside the projection unit 100. Also good.

2. 2. Image Processing Unit 2.1 Outline of Processing FIG. 2 is an explanatory diagram of correction processing performed in the image processing unit 30 in FIG. FIG. 2 schematically shows the horizontal position of the image on the horizontal axis and the saturation level on the vertical axis as the characteristics of the image represented by each image data being corrected. In FIG. 2, illustration of chroma noise, which will be described later, is omitted.

  The input image IMGin is, for example, an image with low saturation on the left side and high saturation on the right side, and has a slight gradation change even in the low saturation area, and a minute gradation change also in the high saturation area. The color compression means C1 performs color compression according to a saturation correction curve indicating the relationship between the saturation component of the input image IMGin before color compression and the saturation component after color compression, and generates an output image IMG1 after color compression. . The color compression means C1 performs color compression so that the original saturation is maintained as much as possible on the low saturation side and color information is not lost as much as possible on the high saturation side. Therefore, the color compression unit C1 performs color compression according to a saturation correction curve as shown in FIG. 2, for example. As a result, in the output image IMG1, the detail portion information is lost on the high saturation side.

Therefore, in the present embodiment, processing for emphasizing a detail portion lost on the high saturation side is performed using the compression rate in the color compression processing performed by the color compression unit C1. Therefore, the signal extracting unit L1, of the luminance component of the image data of the output image IMG1 after color compression by color compression means C1, extracts a signal C _H chroma component in the predetermined spatial frequency band. In Figure 2, corresponding to the spatial frequency is set gain, the signal extracting unit L1 extracts a signal C _H chroma component of this gain is large spatial frequency band.

The saturation gain generation unit G1 generates a gain g corresponding to the compression rate performed by the color compression unit C1. The saturation gain generation means G1 generates the gain g so that it is smaller on the low saturation side and larger as it becomes the higher saturation side. The saturation gain generation unit G1 generates a gain g corresponding to the slope of the saturation correction curve in the color compression processing performed by the color compression unit C1, for example. The multiplier M1 multiplies the signal C _H and the gain g extracted by the signal extracting unit L1, generates the correction data D1 is a correction amount corresponding to the compression ratio. The correction data D1 is data in which the correction amount is small on the low saturation side and the correction amount is large on the high saturation side.

  The adder A1 adds the output image IMG1 (saturation component) after color compression by the color compression means C1 and the correction data D1 to obtain a saturation signal (saturation component) Cout constituting the image data after correction. Output. In this way, the image data with the saturation component corrected is output to the projection unit 100. Thereby, when color compression is performed, the appearance of the detail portion of the image can be improved.

2.2 Configuration example [Overall configuration]
FIG. 3 shows a block diagram of a hardware configuration example of the image processing unit 30 in FIG. FIG. 3 schematically shows the input image data and also shows the projection unit 100. In the following, in the input image data, the pixel value of each pixel is represented by the RGB color system, and each pixel is configured by R component, G component, and B component image data.

  The image processing unit 30 receives input image data 2 generated by an image generation device (not shown). The image processing unit 30 corrects the input image data 2 as described above, and outputs the corrected image data to the projection unit 100. At this time, the color gamut data of the input image of the input source and the color gamut data of the projection unit 100 that is the output destination are acquired, and color compression is performed based on both color gamut data, and the compression at the time of this color compression processing The image data is corrected according to the rate.

  Here, the function of the image generation apparatus is realized by, for example, a personal computer (PC). The input image data 2 includes image data 4 in which each pixel is composed of R component, G component, and B component image data, and color gamut data 6 corresponding to the image data 4. The color gamut data 6 is closed surface data on the CIELAB color space that contains the color gamut of the color space of the input image represented by the image data 4 or the color distribution in the input image. The color gamut data 6 has a known data format such as an ICC (International Color Consortium) profile or GamutID.

  The color gamut data 8 of the projection unit 100 is also provided in advance or inside the projection unit 100 so that the image processing unit 30 can acquire it by any means. The color gamut data 8 is also in the same data format as the color gamut data 6, and has a known data format such as an ICC profile or GamutID. When the data format of the color gamut data 8 is different from the data format of the color gamut data 6, the data format of both color gamut data is changed by a known data format conversion process inside or outside the image processing unit 30, for example. Match. Further, the color gamut data 8 may be generated based on measurement data of an image actually displayed by the projection unit 100.

The image processing unit 30 to which such color gamut data 6 and 8 are input includes an input image color gamut data storage unit 32, a display device color gamut data storage unit 34, a compression rate calculation circuit (compression rate calculation unit) 36, RGB → L ^* C ^* h ^* conversion circuit 40, color compression circuit (color compression unit) 50, line memory 60, L ^* C ^* h ^* → RGB conversion circuit 70, detail enhancement circuit (detail enhancement unit) 200 are included.

  The input image color gamut data storage unit 32 stores the color gamut data 6 constituting the input image data 2 from the image generation apparatus. The display device color gamut data storage unit 34 stores the color gamut data 8 acquired by performing read control on the projection unit 100 and the like.

  The compression rate calculation circuit 36 is based on the color gamut data stored in the input image color gamut data storage unit 32 and the color gamut data stored in the display device color gamut data storage unit 34, and the colors in the color gamut of the input image. Is associated with a color within the color gamut of the projection unit 100. When the data format of the color gamut data stored in the input image color gamut data storage unit 32 is different from the data format of the color gamut data stored in the display device color gamut data storage unit 34, a compression rate calculation circuit. In 36, a conversion process for matching the data formats of both color gamut data is performed.

4A and 4B are diagrams for explaining the operation of the compression rate calculation circuit 36 shown in FIG. In FIG. 4A, the horizontal axis represents the saturation C ^* in the CIELAB color space, and the vertical axis represents the lightness L ^* in the CIELAB color space. The color gamut of the input image data and the color gamut of the projection unit 100 are two-dimensionally represented. It is shown in FIG. 4B shows an example of a saturation correction curve in which the horizontal axis represents saturation before color compression and the vertical axis represents saturation after color compression. 4B, portions corresponding to those in FIG. 4A are denoted by the same reference numerals, and description thereof is omitted as appropriate.

As shown in FIG. 4A, for example, when the color in the color gamut of the input image data is a color outside the color gamut of the projection unit 100, the color needs to be compressed to a color in the color gamut of the projection unit 100. Therefore, the compression rate calculation circuit 36 compresses, for example, the saturation C ^* _{in_max} on the boundary of the gamut of the input image data in the saturation direction to become the saturation C ^* _{out_max} on the boundary of the gamut of the projection unit 100. In this way, a saturation correction curve is generated for each combination of lightness (lightness component) and hue (hue component).

Here, the saturation of the target pixel before color compression is C ^* , the saturation of the target pixel after color compression is F (C ^* ), the maximum saturation of the color gamut of the input image is C ^* _{in_max} , and the projection unit 100 The maximum saturation of the color gamut is C ^* _{out_max} , and the saturation of the boundary between the color compression area and the non-color compression area is C0 ^* . C0 ^* can be C0 ^* = d × C ^* _{out_max} (where d is a constant not less than 0 and less than 1). When C ^* _{out_max} is _{equal to} or greater than C ^* _{in_max} , the compression ratio calculation circuit 36 generates a saturation correction curve as in the following equation. At this time, the compression rate calculation circuit 36 associates the colors in the color gamut of the input image with the colors in the color gamut of the projection unit 100 on a one-to-one basis so that color information is not lost without performing color compression.

In ^contrast, when the _{C * out - max} is less than _{^C *} ^in_max, compression ratio calculating circuit 36 generates a saturation correction curve according to the following equation. In the ^following, _{C * out - max} if _{^C *} ^in_max smaller (i.e., the color gamut of the projection portion 100 may narrower than the color gamut of the input image) will be described.

When the saturation C ^* is equal to or less than C0 ^* , the compression ratio calculation circuit 36 does not perform color compression, and the color in the color gamut of the input image is not lost in the color gamut of the projection unit 100 so that the color information is not lost. Associate with a color. On the other hand, when the saturation C ^* is greater than C0 ^* and the saturation C ^* is _{equal to} or less than C ^* _{in_max} , as shown in FIG. Such a saturation correction curve is generated, and the color in the color gamut of the input image is color-compressed to the color in the color gamut of the projection unit 100. Then, the compression rate calculation circuit 36 obtains the reciprocal of the slopes of some C ^* _in (= ΔC ^* _in / ΔC ^* _out ) as the compression rate α.

In the present embodiment, the saturation correction curve is referred to as a saturation correction curve for convenience of explanation, even if C ^* _in and C ^* _out are linear lines.

In FIG. 3, an RGB → L ^* C ^* h ^* conversion circuit 40 converts the pixel value of each pixel constituting the image data 4 from the RGB color system to the L ^* C ^* h ^* color system in the CIELAB color space. Each pixel value is converted into a lightness signal (lightness component) L ^* , a saturation signal (saturation component) C ^* , and a hue signal (hue component) h ^* in the L ^* C ^* h ^* color system. In the present embodiment, the data format of the pixel value of each pixel of the image data 4 is the RGB format, and processing is performed with the lightness signal L ^* , the saturation signal C ^* , and the hue signal h ^* in the image processing unit 30. However, the present embodiment is not limited to the data format of the image data 4 or the signal format in the image processing unit 30.

The brightness signal L ^* and the hue signal h ^* converted by the RGB → L ^* C ^* h ^* conversion circuit 40 are supplied to the line memory 60, and the line memory 60 receives the RGB → L ^* C ^* h ^* conversion circuit 40. The lightness signal L ^* and the hue signal h ^* are stored.

The lightness signal L ^* , the saturation signal C ^*, and the hue signal h ^* converted by the RGB → L ^* C ^* h ^* conversion circuit 40 are supplied to the color compression circuit 50. The color compression circuit 50 includes a saturation correction curve corresponding to a combination of the lightness signal L ^* and the hue signal h ^* among the saturation correction curves generated by the compression ratio calculation circuit 36 (see, for example, FIG. 4B). Accordingly, the color compression processing is performed on the saturation signal C ^* .

  FIG. 5 shows an operation explanatory diagram of the color compression circuit 50.

The color compression circuit 50 stores the information calculated by the compression rate calculation circuit 36 in, for example, a look-up table (hereinafter referred to as LUT) format, and RGB → L ^* C ^* h ^* conversion circuit 40. The color signal after color compression is output based on the color signal C ^* . More specifically, the color compression circuit 50 receives input values C at a plurality of sampling points on the saturation correction curve calculated by the compression rate calculation circuit 36 for each combination of the lightness signal L ^* and the hue signal h ^{*. *} _In and output value C ^* _out and the compression rate α at each sampling point are stored in the LUT format. When the saturation signal C ^* from the RGB → L ^* C ^* h ^* conversion circuit 40 is input, the color compression circuit 50 causes the lightness signal L ^* from the RGB → L ^* C ^* h ^* conversion circuit 40 and The saturation signal C ^* corresponding to the combination of the hue signal h ^* is set as the input value C ^* _in , and the output value C ^* _out corresponding to this is output.

Note that the color compression circuit 50 performs an interpolation operation by a known interpolation method using information of two sampling points stored in the LUT according to the input value C ^* _in to obtain an output value C ^* _out . Thereby, the color compression circuit 50 can output a saturation signal after color compression according to the saturation correction curve generated by the compression rate calculation circuit 36 for the saturation signal C ^* other than the sampling point. The color compression circuit 50 realizes the function of the color compression unit C1 of FIG.

When the output value C ^* _out is obtained, the color compression circuit 50 also outputs a compression rate α corresponding thereto. The line memory 60 stores the lightness signal L ^* , the hue signal h ^* from the RGB → L ^* C ^* h ^* conversion circuit 40, the chroma signal after color compression from the color compression circuit 50, and the compression ratio in association with each other. To do. The color compression circuit 50 according to the input value C ^* _in, performs known interpolation operation by the interpolation method using the compression ratio in the two sampling points stored in LUT, corresponding to the input value C ^* _in The compression rate α is obtained.

  The detail emphasis circuit 200 performs detail emphasis processing on the chroma signal after color compression stored in the line memory 60. This detail enhancement process amplifies the change of the detail part (detail) according to the compression rate only for the specific frequency component of the saturation signal after color compression, without affecting other parts. This is a process for improving the appearance of detail portions lost during color compression. In this detail emphasis process, noise is extracted and the detail portion is enhanced according to the extracted noise amount, thereby improving the appearance of the detail portion lost during color compression without amplifying the noise.

The chroma signal subjected to the detail emphasis processing by the detail emphasis circuit 200 is a L ^* C ^* h ^* → RGB conversion circuit together with the lightness signal L ^* and the hue signal h ^* stored in the line memory 60 corresponding thereto. 70. The L ^* C ^* h ^* → RGB conversion circuit 70 converts each pixel into a RGB color system pixel value for the input saturation signal, lightness signal L ^*, and hue signal h ^* . The RGB color system pixel values converted by the L ^* C ^* h ^* → RGB conversion circuit 70 are output to the projection unit 100.

2.3 Detailed Configuration Example 2.3.1 Detail Enhancement Circuit FIG. 6 shows a block diagram of a configuration example of the detail enhancement circuit 200 of FIG. 6 also shows the line memory 60 and the L ^* C ^* h ^* → RGB conversion circuit 70 of FIG.

  The detail enhancement circuit 200 includes a noise extraction / removal circuit (saturation noise removal unit) 210, a multistage filter circuit (signal extraction unit) 230, a correction amount calculation circuit (correction amount calculation unit) 250, and a correction circuit (correction unit) 270. Including.

  The noise extraction / removal circuit 210 analyzes the spatial frequency of the saturation signal stored in the line memory 60. More specifically, the noise extraction / removal circuit 210 can extract the high frequency component of the saturation signal and remove the saturation noise from the saturation signal from the line memory 60. The output highC, which is the absolute value of the high frequency component of the saturation signal extracted by the noise extraction / removal circuit 210, is supplied to the correction amount calculation circuit 250 as the analysis result of the noise extraction / removal circuit 210. The saturation signal from which the saturation noise has been removed by the noise extraction / removal circuit 210 is supplied to the correction circuit 270 as the saturation signal NR.

  The multistage filter circuit 230 extracts a signal in a given spatial frequency band from the saturation signal (saturation signal after color compression) stored in the line memory 60. This multistage filter circuit 230 realizes the function of the signal extraction means L1 of FIG.

  The correction amount calculation circuit 250 corresponds to the saturation signal correction amount based on the output of the multistage filter circuit 230, the compression rate stored in the line memory 60, and the analysis result of the noise extraction / removal circuit 210. Correction data VA is calculated. That is, the correction amount calculation circuit 250 corrects the saturation signal in a given spatial frequency band extracted by the multistage filter circuit 230 according to the output highC (analysis result of the noise extraction / removal circuit 210) and the compression rate α. The amount can be calculated. The correction amount calculation circuit 250 can realize the function of the saturation gain generation unit G1 shown in FIG.

  The correction circuit 270 corrects the saturation signal NR from which the saturation noise has been removed by the noise extraction / removal circuit 210, using the correction data calculated by the correction amount calculation circuit 250, and the saturation signal after the detail enhancement processing Output as.

The saturation signal that has been subjected to the detail enhancement processing by the detail enhancement circuit 200 and the lightness signal L ^* and the hue signal h ^* stored in the line memory 60 corresponding to the saturation signal are expressed as L ^* C ^* h. ^* → Supplied to the RGB conversion circuit 70.

  Below, each part which comprises the detail emphasis circuit 200 is demonstrated in detail.

[Noise removal / extraction circuit]
FIG. 7 shows a block diagram of a configuration example of the noise extraction / removal circuit 210 of FIG. FIG. 7 also shows the line memory 60 together. In FIG. 7, the same parts as those in FIG. 6 are denoted by the same reference numerals, and description thereof will be omitted as appropriate.

  The noise extraction / removal circuit 210 includes a high-frequency component extraction circuit (high-frequency component extraction unit) 212 and a saturation noise removal circuit (saturation noise removal unit) 220. The high frequency component extraction circuit 212 extracts a given high frequency component including saturation noise from the saturation signal stored in the line memory 60, and outputs the absolute value as an output highC. The saturation noise removal circuit 220 generates a saturation signal NR from which saturation noise is removed from the saturation signal stored in the line memory 60. At this time, the saturation noise removal circuit 220 generates a saturation signal NR using the high frequency component extracted by the high frequency component extraction circuit 212.

The high frequency component extraction circuit 212 includes a high pass filter (hereinafter abbreviated as HPF) circuit 214. The saturation signal is input to the HPF circuit 214 from the line memory 60, and the absolute value of the high frequency component of the saturation signal is output as highC and output to the correction amount calculation circuit 250 and the saturation noise removal circuit 220. Such an HPF circuit 214 outputs an output highC as an absolute value of a high-frequency component according to the following equation by a known HPF process.

Here, highC is the output of the HPF circuit 214, C is the input saturation signal, (x, y) is the coordinates of the target pixel, a _HPF is the filter coefficient, and (u, v) is relative to the target pixel. Taking the above range in the coordinate system, s represents the size of the filter. For example, s may be “3”, but may be other than “3”.

The saturation noise removal circuit 220 includes a low pass filter (hereinafter referred to as LPF) circuit 222, a weight calculation circuit 224, multipliers 226 and 227, and an adder 228. The saturation signal is input to the LPF circuit 222 from the line memory 60, and the low frequency component of the saturation signal is passed through. Such an LPF circuit 222 outputs an output lowC according to the following equation by a known LPF process.

Here, lowC is the output of the LPF circuit 222, C is the input saturation signal, (x, y) is the coordinates of the target pixel, a _LPF is the filter coefficient, and (u, v) is relative to the target pixel. Taking the above range in the coordinate system, s represents the size of the filter. For example, s may be “5”, but may be other than “5” and is preferably larger than the filter size of the HPF circuit 214.

  It is desirable that the filter characteristics of the HPF circuit 214 and the filter characteristics of the LPF circuit 222 in FIG. 7 have the following relationship.

  FIG. 8 shows an example of the filter characteristics of the HPF circuit 214 and the LPF circuit 222 shown in FIG. In FIG. 8, the horizontal axis represents the frequency of the saturation signal and the vertical axis represents the gain.

The output of the HPF circuit 214 is small in a region where the spatial frequency of the saturation signal is low, and is large in a region where the spatial frequency of the saturation signal is high (T1 in FIG. 8). The cutoff frequency of the HPF circuit 214 is ω _HPF . On the other hand, the output of the LPF circuit 222 increases in a region where the spatial frequency of the saturation signal is low, and decreases in a region where the spatial frequency of the saturation signal is high (T2 in FIG. 8). The cut-off frequency of the LPF circuit 222 is ω _LPF . Here, it is desirable that the cutoff frequency of the HPF circuit 214 is equal to the cutoff frequency of the LPF circuit 222 (ω _HPF = ω _LPF = ω _cut ). As a result, the saturation signal can be corrected without losing information of the original saturation signal.

  Returning to FIG. 7, the description will be continued. The weight calculation circuit 224 calculates a weight amount in accordance with the output from the high frequency component extraction circuit 212. The weighting calculation circuit 224 stores the weighting amount corresponding to the output highC of the HPF circuit 214 in the LUT format, reads a value corresponding to the output from the HPF circuit 214, or a plurality of values corresponding to the output from the HPF circuit 214. The value of can be interpolated and output.

  FIG. 9 is a diagram for explaining the operation of the weight calculation circuit 224.

The weight calculation circuit 224 outputs a weighting coefficient K _LPF to the multiplier 226 and outputs a weighting coefficient K _HPF to the multiplier 227 according to the output of the HPF circuit 214. More specifically, the weighting calculation circuit 224 stores weighting coefficients K _HPF and K _LPF corresponding to the output from the HPF circuit 214 in advance in the LUT format. That is, the weighting calculation circuit 224 has weighting coefficients (K _HPF a, K _LPF a), (K _HPF b, K _LPF b), (K _HPF c, K _LPF c), corresponding to the output of the HPF circuit 214 in advance. Are stored, and when the output highC of the HPF circuit 214 is input, the weighting coefficients K _HPF and K _LPF corresponding thereto are output.

FIG. 10 is an explanatory diagram of the weighting coefficients K _HPF and K _LPF output from the weight calculation circuit 224 described in FIG. In FIG. 10, the horizontal axis represents the output of the HPF circuit 214, and the vertical axis represents the weighting coefficients K _HPF and K _LPF as the weighting amounts output from the weight calculation circuit 224.

The weighting calculation circuit 224 stores a weighting coefficient K _HPF that increases as the output highC of the HPF circuit 214 increases (T10 in FIG. 10), and decreases as the output highC of the HPF circuit 214 increases. The weighting coefficient K _LPF is stored (T11 in FIG. 10). In FIG. 10, the weighting coefficient _K HPF according to the output highC HPF circuit _214, although _{K LPF} is increased or decreased linearly weighting factor _{K HPF, K LPF} is increased or decreased in accordance with a given function It may be.

In FIG. 7, the multiplier 226 outputs the multiplication result of the output of the LPF circuit 222 and the weighting coefficient K _LPF from the weight calculation circuit 224 and outputs the result to the adder 228. The multiplier 227 outputs the multiplication result of the output of the HPF circuit 214 and the weighting coefficient K _HPF from the weight calculation circuit 224 and outputs the result to the adder 228. The adder 228 adds the multiplication result of the multiplier 226 and the multiplication result of the multiplier 227, and outputs the result as a saturation signal NR after removing saturation noise. That is, when the output of the HPF circuit 214 is highC and the output of the LPF circuit 222 is lowC, the saturation noise removal circuit 220 outputs a saturation signal NR according to the following equation.

As described above, since the weight calculation circuit 224 outputs the weighting coefficients K _HPF and K _LPF as shown in FIG. 10, the saturation signal NR is a signal from which high-frequency saturation noise has been removed. The region where the output highC of the HPF circuit 214 is small is a region where there are many low frequency components. Since a minute high-frequency component in such a region is likely to be noise, the weighting coefficient K _HPF is reduced to remove the noise. That is, by reducing the weighting coefficient K _HPF and increasing the weighting coefficient K _LPF , it is possible to obtain a desired saturation signal NR without enhancing saturation noise. On the other hand, the region where the output highC of the HPF circuit 214 is large is a region where there are many high-frequency components. Since the high-frequency component in such a region is likely to be original image data, the weighting coefficient K _HPF is increased. That is, a desired saturation signal NR can be obtained by increasing the weighting coefficient K _HPF and decreasing the weighting coefficient K _LPF .

  In FIG. 7, the noise extraction / removal circuit 210 has been described as having a configuration including a high-frequency component extraction circuit 212 and a saturation noise removal circuit 220. The saturation signal stored in the line memory 60 may be output as it is to the correction circuit 270 as the saturation signal NR.

[Multi-stage filter circuit]
FIG. 11 is a block diagram showing a configuration example of the multistage filter circuit 230 shown in FIG. FIG. 11 also shows the line memory 60. In FIG. 11, the same parts as those in FIG.

  The multistage filter circuit 230 includes a first filter circuit 232, a second filter circuit 234, and a third filter circuit 236 having different filter sizes. FIG. 11 illustrates an example in which the multistage filter circuit 230 performs filter processing using three types of filter circuits, but the present embodiment is not limited to the number of filter circuits. That is, the multi-stage filter circuit 230 includes a plurality of filter circuits having different frequency bands of signals to be extracted, and each filter circuit includes pixel values of pixels arranged in the horizontal and vertical directions of the image, a filter coefficient matrix, and the like. It is sufficient if the result of the convolution operation can be output.

The first filter circuit 232 can output the filtered result according to the following equation.

  In the above equation, the output of the first filter circuit 232 is FO1, the saturation signal of coordinates (x, y) is C (x, y), the filter coefficients are a, and (i, j) are centered on the target pixel. Take the range of the above equation in relative coordinates and let the filter size be s. Each filter circuit receives a saturation signal having the number of lines corresponding to the filter size (the number of vertical scanning lines).

  Although the above expression shows the output of the first filter circuit 232, the second filter circuit 234 and the third filter circuit 236 can also output the same filter processing result except for the filter size. (Outputs FO2, FO3).

  In the present embodiment, the filter size of the first filter circuit 232 is “3”, the filter size of the second filter circuit 234 is “5”, and the filter size of the third filter circuit 236 is “7”. However, the present embodiment is not limited to the filter sizes of the filter circuits of the first filter circuit 232, the second filter circuit 234, and the third filter circuit 236.

[Correction amount calculation circuit]
FIG. 12 shows a block diagram of a configuration example of the correction amount calculation circuit 250 of FIG. In FIG. 12, the same parts as those of FIG. In FIG. 12, the line memory 60, the multistage filter circuit 230, and the noise extraction / removal circuit 210 are shown together.
FIG. 13 is a diagram for explaining the operation of the weight calculation circuit 252 in FIG.
FIG. 14 shows an operation explanatory diagram of the saturation gain calculation circuit 260 of FIG.

The correction amount calculation circuit 250 includes a weight calculation circuit 252, multipliers 254 _{1 to} 254 ₃ , an adder 256, a multiplier 258, and a saturation gain calculation circuit 260.

The output highC generated by the HPF circuit 214 of the high frequency component extraction circuit 212 of the noise extraction / removal circuit 210 is input to the weight calculation circuit 252. Then, the weighting calculation circuit 252 calculates the weighting coefficients g _{1 to} g ₃ according to the output highC from the HPF circuit 214, as shown in FIG. Such a weight calculation circuit 252 is realized by an LUT in which the input is the output highC from the HPF circuit 214 and the outputs are the weighting coefficients g _{1 to} g ₃ . Therefore, the weighting calculation circuit 252 includes weighting coefficients (g ₁ a, g ₂ a, g ₃ a), (g ₁ b, g ₂ b, g ₃ b) corresponding to the output highC from the HPF circuit 214 in advance. (G ₁ c, g ₂ c, g ₃ c),... Are stored, and when an output highC is input from the HPF circuit 214, a weighting coefficient corresponding to the output highC is output.

  For example, it is desirable that the weighting calculation circuit 252 outputs a weighting coefficient that increases as the amount of the saturation noise component decreases, based on the output highC of the HPF circuit 214. As a result, the saturation component correction amount calculation circuit 250 can increase the saturation component correction amount (amplification amount) as the amount of the saturation noise component removed by the noise extraction / removal circuit 210 decreases.

Adder 256 adds the multiplication results of multipliers 254 _{1 to} 254 ₃ and outputs the addition result to multiplier 258. The multiplier 258 further receives the saturation gain coefficient h calculated by the saturation gain calculation circuit 260.

  The saturation gain calculation circuit 260 receives the compression rate α stored in the line memory 60. Then, as shown in FIG. 14, the saturation gain calculation circuit 260 calculates a saturation gain h according to the compression rate α from the line memory 60.

  Such a saturation gain calculation circuit 260 is realized by an LUT having an input as the compression rate α from the line memory 60 and an output as the saturation gain h. Therefore, saturation gains ha, hb, hc,... Corresponding to the compression rate α from the line memory 60 are stored in advance in the saturation gain calculation circuit 260, and the compression rate α is input from the line memory 60. When this is done, a saturation gain corresponding to this is output.

It is desirable that the saturation gain calculation circuit 260 outputs a saturation gain h expressed by the following equation with respect to the compression rate α.

  With the saturation gain h calculated according to the above equation, the saturation component correction amount (amplification amount) can be increased as the compression rate increases. That is, even when the detail portion is crushed by color compression, the correction data VA increases accordingly, and the appearance of the detail can be improved.

  In FIG. 12, a multiplier 258 multiplies the addition result of the adder 256 by the saturation gain h from the saturation gain calculation circuit 260, and uses the multiplication result as correction data VA corresponding to the correction amount of the saturation signal. Output as. The correction data VA is input to the correction circuit 270. The correction circuit 270 adds the correction data VA to the saturation signal NR from which the saturation noise component has been removed by the noise extraction / removal circuit 210, and outputs the result as a corrected saturation signal.

  As described above, the correction amount calculation circuit 250 corresponds to the signal in the given spatial frequency band extracted by the multistage filter circuit 230 (signal extraction circuit in a broad sense) and the saturation corresponding to the compression rate α in the color compression processing. Based on the saturation gain coefficient calculated by the gain calculation circuit 260, the correction amount of the saturation signal can be calculated.

  The correction amount calculation circuit 250 is not limited to the configuration shown in FIG. For example, in FIG. 12, the weight calculation circuit 252 may be input with FO1 to FO3 from the multistage filter circuit 230.

  FIG. 15 is an explanatory diagram of the effect of the detail enhancement processing of the image processing unit 30 in the present embodiment. In FIG. 15, the horizontal axis represents the output level of the HPF circuit 214, and the vertical axis represents the spatial frequency of the saturation signal.

  In the present embodiment, the saturation is maintained as it is in the low frequency region of the saturation signal. On the other hand, the appearance of the detail portion of the image is improved by performing correction over the high frequency region of the saturation signal. At this time, it is determined that the higher the output level of the HPF circuit 214 in the high-frequency region of the saturation signal, the more saturation noise is present, and the saturation component in which the output level of the HPF circuit 214 is from the low level to the medium level is given. Is corrected for the signal in the level range Far.

  Therefore, as shown in FIG. 15, in the region where the output level of the HPF circuit 214 is high, the saturation signal is not corrected to avoid amplifying the saturation noise, while the output level of the HPF circuit 214 is medium. The saturation signal is corrected from the level to the small level region. Here, by correcting so that the correction amount (amplification amount) of the saturation signal in the high frequency region is larger than that in the low frequency region, it is possible to improve the appearance of the detail portion of the color-compressed image.

  The processing of the image processing unit 30 having the above configuration can also be realized by software processing. In this case, the image processing unit 30 includes a central processing unit (hereinafter abbreviated as “CPU”), a read only memory (hereinafter abbreviated as “ROM”), or a random access memory (hereinafter “Random Access Memory”). CPU, which reads a program stored in ROM or RAM, controls hardware such as a multiplier and an adder by executing processing corresponding to the program, and Perform correction processing of the degree component.

  FIG. 16 shows a flowchart of a processing example of the image processing unit 30 in the present embodiment. When the processing in FIG. 16 is realized by software, a program for realizing the processing shown in FIG. 16 is stored in a ROM or RAM built in the image processing unit 30.

  First, the image processing unit 30 acquires the color gamut data of the input image and the color gamut data of the projection unit 100 as a color gamut data acquisition step (step S10). The color gamut data acquired in step S10 is stored in a RAM built in the image processing unit 30. At this time, the data format of both gamut data has a known data format such as an ICC profile or GamutID. If the data formats are different from each other, conversion processing is performed to match the data formats of both gamut data.

Next, as described in FIGS. 4A and 4B, the image processing unit 30 generates a saturation correction curve for each combination of brightness and hue as the saturation correction curve generation step (step). S12). That is, the image processing unit 30 sets the saturation C ^* _{in_max} on the boundary of the color gamut of the input image data based on the color gamut data of the input image acquired in step S10 and the color gamut data of the projection unit 100. A saturation correction curve is generated so that the saturation C ^* _{out_max} on the boundary of the color gamut of the projection unit 100 is obtained by compressing in the degree direction.

Thereafter, the image processing unit 30 calculates a compression rate α for each saturation correction curve generated in step S12 as a compression rate calculation step (step S14). This compression rate α corresponds to the reciprocal of the slope at some C ^* _in (= ΔC ^* _in / ΔC ^* _out ) _in each saturation correction curve.

Subsequently, the image processing unit 30 starts accepting input image data corresponding to the input image as an input image data accepting step (step S16). Here, it is assumed that the pixel value of each pixel is expressed in the RGB color system. When the input image data is received in step S16, the image processing unit 30 converts the pixel value of each pixel of the input image data represented by the RGB color system into the L ^* C ^* h ^* color system, and the brightness signal. L ^* , saturation signal C ^* and hue signal h ^* are calculated (step S18).

The image processing unit 30 then follows the saturation correction curve corresponding to the combination of the lightness signal L ^* and the hue signal h ^* converted in step S18 among the saturation correction curves generated in step S12 as the color compression step. Then, color compression processing is performed on the saturation signal C ^* converted in step S18 (step S20). As a result, the saturation signal obtained by performing color compression processing on the saturation signal C ^* converted in step S18 and the compression rate corresponding to the slope on the saturation correction curve used in this color compression processing are acquired.

  As the detail emphasis processing step, the image processing unit 30 calculates the saturation signal after the color compression processing obtained as a result of the color compression processing in step S20 and the slope on the saturation correction curve used in this color compression processing. Detail emphasis processing is performed using the corresponding compression ratio (step S22).

Thereafter, the image processing unit 30 converts the saturation signal after the detail enhancement processing into the RGB color system together with the lightness signal L ^* and the hue signal h ^* corresponding to the saturation signal (step S24), and the projection unit 100. The RGB color system pixel value is output to (step S26).

  Here, when the process ends (step S28: Y), the image processing unit 30 ends the series of processes (end). When the process does not end (step S28: N), the process returns to step S16 and continues the process. .

  FIG. 17 shows a flowchart of a processing example of the detail emphasis processing of FIG. 16 of the image processing unit 30 in the present embodiment. The process shown in FIG. 17 is performed in step S22 of FIG. When the processing in FIG. 17 is realized by software, a program for realizing the processing shown in FIG. 17 is stored in a ROM or RAM built in the image processing unit 30.

  When the detail enhancement process is performed in step S22, the image processing unit 30 first extracts a specific spatial frequency band of the saturation signal as a signal extraction step (step S40). For example, when the saturation signal of a given spatial frequency band is extracted by the multistage filter circuit 230 or realized by software processing, a multiplier or an adder that realizes the function of the multistage filter circuit 230 is used by the CPU. The saturation signal of the spatial frequency band is extracted by controlling.

  Thereafter, the image processing unit 30 analyzes the spatial frequency of the saturation signal (steps S42 and S44). More specifically, in step S42, the image processing unit 30 extracts a saturation signal of a given high-frequency component from the saturation signal after color compression as a high-frequency component extraction step. In step S44, the image processing unit 30 removes a saturation noise component from the saturation signal after color compression as a saturation noise removal step.

  Then, as the saturation gain calculation step, the image processing unit 30 calculates a saturation gain corresponding to the compression rate α calculated in step S14 of FIG. 16 (step S46). Next, the image processing unit 30 calculates correction data corresponding to the correction amount of the saturation signal using the saturation gain calculated in step S46 as the saturation component correction amount calculation step (step S48). That is, in step S48, the image processing unit 30 weights the signal in a given spatial frequency band with a coefficient corresponding to the high-frequency component saturation signal (output highC of the HPF circuit 214) extracted in step S42. The correction data VA is generated by multiplying the saturation gain calculated in step S46. Alternatively, when realized by software processing, the CPU weights the signal extracted by the signal extraction processing with a coefficient corresponding to the saturation signal of the high frequency component extracted in step S42, and then calculates in step S46. The saturation gain is multiplied and output as correction data VA.

  Then, the image processing unit 30 corrects the saturation signal from which the saturation noise has been removed in step S44, using the correction data VA corresponding to the correction amount calculated in step S48 as the saturation component correction step ( In step S50), the corrected saturation signal is output (step S52), and the series of processing ends (end). That is, in step S50, the correction circuit 270 adds a correction signal corresponding to the correction data VA to the saturation signal after the color compression process, and generates a corrected saturation signal. Alternatively, when realized by software processing, the CPU generates a corrected saturation signal by adding a correction signal corresponding to the correction data VA to the saturation signal after the color compression processing.

  In the processing shown in FIG. 16 or FIG. 17, the same processing can be realized even if the order of each step is appropriately changed.

  The RGB color system image data in which the pixel value of each pixel is corrected in this way is output to the projection unit 100. The projection unit 100 modulates the light from the light source based on the image data from the image processing unit 30, and projects the modulated light onto the screen SCR.

3. Projection Unit FIG. 18 shows a diagram of a configuration example of the projection unit 100 of FIG. 1 or FIG. In FIG. 18, the projection unit 100 according to the present embodiment is described as being configured by a so-called three-plate type liquid crystal projector, but the projection unit as the image output device according to the present invention is configured by a so-called three-plate type liquid crystal projector. It is not limited to the thing. That is, in the following description, it is assumed that one pixel is composed of an R component sub-pixel, a G component sub-pixel, and a B component sub-pixel, but the number of sub-pixels (color component number) constituting one pixel is described. It is not limited.

  The projection unit 100 includes a light source 110, integrator lenses 112 and 114, a polarization conversion element 116, a superimposing lens 118, an R dichroic mirror 120R, a G dichroic mirror 120G, a reflection mirror 122, an R field lens 124R, and a G field lens 124G. , R liquid crystal panel 130R (first light modulation element), G liquid crystal panel 130G (second light modulation element), B liquid crystal panel 130B (third light modulation element), relay optical system 140, cross dichroic A prism 160 and a projection lens 170 are included. The liquid crystal panels used as the R liquid crystal panel 130R, the G liquid crystal panel 130G, and the B liquid crystal panel 130B are transmissive liquid crystal display devices. The relay optical system 140 includes relay lenses 142, 144, and 146 and reflection mirrors 148 and 150.

  The light source 110 is composed of, for example, an ultra-high pressure mercury lamp, and emits light including at least R component light, G component light, and B component light. The integrator lens 112 has a plurality of small lenses for dividing the light from the light source 110 into a plurality of partial lights. The integrator lens 114 has a plurality of small lenses corresponding to the plurality of small lenses of the integrator lens 112. The superimposing lens 118 superimposes the partial light emitted from the plurality of small lenses of the integrator lens 112 on the liquid crystal panel.

  The polarization conversion element 116 has a polarization beam splitter array and a λ / 2 plate, and converts light from the light source 110 into substantially one type of polarized light. The polarization beam splitter array has a structure in which a polarization separation film that separates the partial light divided by the integrator lens 112 into p-polarization and s-polarization, and a reflection film that changes the direction of the light from the polarization separation film are alternately arranged. Have. The polarization direction of the two types of polarized light separated by the polarization separation film is aligned by the λ / 2 plate. Light that has been converted into substantially one type of polarized light by the polarization conversion element 116 is applied to the superimposing lens 118.

  The light from the superimposing lens 118 enters the R dichroic mirror 120R. The R dichroic mirror 120R has a function of reflecting R component light and transmitting G component and B component light. The light transmitted through the R dichroic mirror 120R is applied to the G dichroic mirror 120G, and the light reflected by the R dichroic mirror 120R is reflected by the reflection mirror 122 and guided to the R field lens 124R.

  The dichroic mirror for G 120G has a function of reflecting G component light and transmitting B component light. The light transmitted through the G dichroic mirror 120G enters the relay optical system 140, and the light reflected by the G dichroic mirror 120G is guided to the G field lens 124G.

  In the relay optical system 140, in order to minimize the difference between the optical path length of the B component light transmitted through the G dichroic mirror 120G and the optical path length of the other R component and G component light, the relay lenses 142, 144, 146 is used to correct the difference in optical path length. The light transmitted through the relay lens 142 is guided to the relay lens 144 by the reflection mirror 148. The light transmitted through the relay lens 144 is guided to the relay lens 146 by the reflection mirror 150. The light transmitted through the relay lens 146 is applied to the B liquid crystal panel 130B.

  The light applied to the R field lens 124R is converted into parallel light and is incident on the R liquid crystal panel 130R. The R liquid crystal panel 130R functions as a light modulation element (light modulation unit), and the transmittance (passage rate, modulation rate) changes based on the R image signal. Therefore, the light (first color component light) incident on the R liquid crystal panel 130R is modulated based on the R image signal, and the modulated light is incident on the cross dichroic prism 160.

  The light applied to the G field lens 124G is converted into parallel light and is incident on the G liquid crystal panel 130G. The G liquid crystal panel 130G functions as a light modulation element (light modulation unit), and the transmittance (passage rate, modulation rate) changes based on the G image signal. Therefore, the light (second color component light) incident on the G liquid crystal panel 130G is modulated based on the G image signal, and the modulated light is incident on the cross dichroic prism 160.

  The B liquid crystal panel 130B irradiated with the light converted into parallel light by the relay lenses 142, 144, and 146 functions as a light modulation element (light modulation unit), and has a transmittance (passage rate) based on the B image signal. , Modulation rate) is changed. Therefore, the light (third color component light) incident on the B liquid crystal panel 130B is modulated based on the B image signal, and the modulated light is incident on the cross dichroic prism 160.

  The R liquid crystal panel 130R, the G liquid crystal panel 130G, and the B liquid crystal panel 130B have the same configuration. Each liquid crystal panel is a liquid crystal, which is an electro-optic material, sealed and encapsulated in a pair of transparent glass substrates. For example, a polysilicon thin film transistor is used as a switching element, and each color light passes corresponding to the image signal of each sub-pixel. Modulate rate.

  In this embodiment, a liquid crystal panel as a light modulation element is provided for each color component constituting one pixel, and the transmittance of each liquid crystal panel is controlled by an image signal corresponding to a sub pixel. That is, the image signal for the R component sub-pixel is used to control the transmittance (transmission rate, modulation factor) of the R liquid crystal panel 130R, and the image signal for the G component sub pixel is used for the G liquid crystal panel 130G. The B component sub-pixel image signal is used to control the transmittance of the B liquid crystal panel 130B.

  The cross dichroic prism 160 has a function of outputting combined light obtained by combining incident light from the R liquid crystal panel 130R, the G liquid crystal panel 130G, and the B liquid crystal panel 130B as outgoing light. The projection lens 170 is a lens that enlarges and forms an output image on the screen SCR.

  Since the image is displayed by the projection unit 100 having the above-described configuration based on the image data corrected by the image processing unit 30 in the present embodiment, even if color compression is performed, the image is lost due to color compression. The appearance of broken details can be improved. In addition, by amplifying the change in the detail part only for the specific frequency component of the saturation signal after color compression, the appearance of the detail part lost during color compression is improved without affecting other parts. can do. Further, by extracting the noise and emphasizing the detail portion according to the extracted noise amount, it is possible to improve the appearance of the detail portion lost during color compression without amplifying the noise.

  In addition, after performing the saturation signal correction process in the present embodiment, by controlling the projection unit 100 as an image display step and displaying an image based on the image data after the correction process, It is possible to provide an image display method that improves the expression of image details without affecting the saturation area that is not subject to correction.

4). Modified Example 4.1 First Modified Example In the image processing unit 30 according to the present embodiment, the correction amount calculating circuit 250 includes a weighting calculating circuit 252 and a saturation gain calculating circuit 260, as shown in FIG. Although the correction data VA is generated by the multiplier that multiplies the weighting coefficient and the saturation gain coefficient, the present embodiment is not limited to this.

  FIG. 19 is a block diagram showing a configuration example of the correction amount calculation circuit 250a in the first modification of the present embodiment. For example, instead of the correction amount calculation circuit 250 in the present embodiment, a correction amount calculation circuit 250a shown in FIG. 19 is built in the detail enhancement circuit 200 of FIG.

The correction amount calculation circuit 250 a includes first to third LUTs 302 ₁ to 302 ₃ , multipliers 304 _{1 to} 304 ₃ , and an adder 306. The correction amount calculation circuit 250a multiplies each output of the multistage filter circuit 230 by the saturation gain coefficient from each of the _{first to third} LUTs 302 ₁ to 302 ₃ , and then adds each multiplication result to perform correction. Output as data VA.

FIGS. 20A, 20B, and 20C are explanatory diagrams of operations of the _{first to third} LUTs 302 ₁ to 302 ₃ in FIG. FIG. 20 (A) represents a first LUT302 operation explanatory diagram of _one of Figure 19. FIG. 20 (B) represents a second LUT302 Operation Figure ₂ of Figure 19. FIG. 20 (C) represents a view for explaining an operation of the third LUT 302 ₃ in FIG. 19.

The first LUT 302 _1, the compression ratio from the output highC and the line memory 60 from the HPF circuit 214 alpha, and outputs a chroma gain coefficient _{j 1} corresponding to the output highC and compression ratio alpha. Therefore, the saturation gain coefficients j ₁ a, j ₁ b, j ₁ c... Corresponding to the output highC and the compression rate α are stored in advance in the first LUT 302 ₁ , and the output highC and the compression rate α. There and outputs a chroma gain coefficient corresponding to the combination of the output highC and compression ratio α when entered as saturation gain coefficient j _1.

The second LUT 302 _2, the compression ratio from the output highC and the line memory 60 from the HPF circuit 214 alpha, and outputs a chroma gain coefficient _{j 1} corresponding to the output highC and compression ratio alpha. Therefore, the second LUT 302 _2, pre-output highC and compression ratio α saturation gain coefficient _j 2 _a corresponding to, j 2 _{b, j} 2 c · · · are stored, the output highC and compression ratio α There and outputs a chroma gain coefficient corresponding to the combination of the output highC and compression ratio α when entered as saturation gain coefficient j _2.

The third LUT 302 _3, the compression ratio from the output highC and the line memory 60 from the HPF circuit 214 alpha, and outputs a chroma gain coefficient _{j 1} corresponding to the output highC and compression ratio alpha. Therefore, the third LUT 302 _3, chroma gain coefficients _j 3 _a corresponding to α advance output highC and compressibility, j 3 _{b, j} 3 c · · · are stored, the output highC and compression ratio α There and outputs a chroma gain coefficient corresponding to the combination of the output highC and compression ratio α when entered as saturation gain coefficient j _3.

19, the multiplier 304 ₁ multiplies the chroma gain coefficient _{j 1} from the output FO1 the first LUT 302 ₁ of the first filter circuit 232 which constitutes the multi-stage filter circuit 230, an adder multiplication result To 306. The multiplier 304 ₂ multiplies the chroma gain coefficient _{j 2} from the output FO2 and the second LUT 302 ₂ of the second filter circuit 234 which constitutes the multi-stage filter circuit 230, and outputs the multiplication result to the adder 306 . The multiplier 304 ₃ multiplies the chroma gain coefficient _{j 3} from the output FO3 the third LUT 302 ₃ of the third filter circuit 236 which constitutes the multi-stage filter circuit 230, and outputs the multiplication result to the adder 306 .

The adder 306 adds the multiplication results of the multipliers 304 _{1 to} 304 ₃ and outputs the addition result as correction data VA.

  As described above, in the image processing unit in the first modification of the present embodiment, the correction amount calculation circuit 250a is provided for each output of the multistage filter circuit 230, and corresponds to the output highC and the compression rate α of the HPF circuit 214. A plurality of tables for outputting the gains, a plurality of multipliers for multiplying each output of the multistage filter circuit 230 provided for each output of the multistage filter circuit 230 and an output of each table constituting the plurality of tables, And an adder for adding the multiplication results of the plurality of multipliers, and the output of the adder can be calculated as a correction amount of the saturation component.

  According to the first modified example of the present embodiment, as in the first embodiment, only the saturation signal in a given spatial frequency band can be corrected according to the compression rate α at the time of color compression. As a result, it is possible to improve the appearance of detail portions lost during color compression without affecting other portions. Furthermore, by extracting noise and emphasizing the detail portion according to the extracted noise amount, it is possible to improve the appearance of the detail portion lost during color compression without amplifying the noise. Furthermore, according to the first modification of the present embodiment, the number of multipliers built in the correction amount calculation circuit can be reduced compared to the first embodiment, so that power consumption and cost can be reduced. Is possible.

4.2 Second Modification As shown in FIG. 19, the correction amount calculation circuit 250 a in the first modification of the present embodiment includes first to third LUTs 302 ₁ to 302 ₃ and multipliers 304 ₁ to 304 ₁ . 304 ₃ and an adder 306, and the multiplication results of the multipliers using the saturation gain coefficients from the _{first to third} LUTs 302 ₁ to 302 ₃ are added. It is not limited to this.

  FIG. 21 shows a block diagram of a configuration example of the correction amount calculation circuit 250b in the second modification example of the present embodiment. For example, instead of the correction amount calculation circuit 250 in the present embodiment, a correction amount calculation circuit 250b shown in FIG. 21 is built in the detail enhancement circuit 200 of FIG.

  The correction amount calculation circuit 250b includes an LUT 352. The correction amount calculation circuit 250b outputs the output from the LUT 352 as correction data VA.

  FIG. 22 is an operation explanatory diagram of the LUT 352 of FIG.

  The LUT 352 includes an output highC from the HPF circuit 214, a compression rate α from the line memory 60, and outputs FO 1 to FO 1 of the first filter circuit 232 to the third filter circuit 236 constituting the multistage filter circuit 230. FO3 is input, and correction data corresponding to the combination of the output highC, the compression rate α, and the output of each filter circuit is output. This correction data is output as correction data VA. Therefore, in the LUT 352, correction data VAa, VAb, ..., VAc, VAd, ..., VAe, VAf, ... corresponding to combinations of highC, compression rate α, and outputs FO1 to FO3 of each filter circuit are stored in advance. .., VAj... Are stored, and when highC, compression rate α, and outputs FO1 to FO3 of each filter circuit are input, correction data corresponding to these combinations is output.

  As described above, in the image processing unit according to the second modification of the present embodiment, the correction amount calculation circuit 250b has saturation corresponding to the output of the multistage filter circuit 230, the output highC of the HPF circuit 214, and the compression rate α. A table for outputting component correction data may be included. Then, the correction data output by this table is output as correction data VA.

  According to the second modification of the present embodiment, as in the present embodiment or the first modification of the present embodiment, only a saturation signal in a given spatial frequency band is compressed with a compression rate α during color compression. It can be corrected according to. As a result, it is possible to improve the appearance of detail portions lost during color compression without affecting other portions. Furthermore, by extracting noise and emphasizing the detail portion according to the extracted noise amount, it is possible to improve the appearance of the detail portion lost during color compression without amplifying the noise. Furthermore, according to the second modification of the present embodiment, the multiplier and the adder built in the correction amount calculation circuit can be eliminated as compared with the first modification of the first embodiment or the first embodiment. Therefore, it is possible to significantly reduce power consumption and cost.

4.3 Third Modification In the present embodiment or its modification, the compression rate α has been described as being the slope at C ^* _in on the saturation correction curve, but the present embodiment is not limited to this. It is not something.

  FIG. 23 is an explanatory diagram of the compression rate α in the third modification of the present embodiment. FIG. 23 shows an example of a saturation correction curve with the horizontal axis representing the saturation before color compression and the vertical axis representing the saturation after color compression. In FIG. 23, portions corresponding to those in FIG. 4B are denoted by the same reference numerals, and description thereof will be omitted as appropriate.

In the third modification of the present embodiment, a saturation correction curve similar to that of the present embodiment is generated by the compression rate calculation circuit. When the saturation C ^* is equal to or lower than C0 ^* , the compression rate calculation circuit does not perform color compression, and the colors in the color gamut of the input image are not lost in the color gamut of the projection unit 100 so that the color information is not lost. Correspond to the color. On the other hand, when the saturation C ^* is larger than C0 ^* and the saturation C ^* is _{equal to} or less than C ^* _{in_max, the higher} the saturation is, as shown in FIG. 23, according to the same equation as FIG. A saturation correction curve is generated so as to reduce the color and the color within the color gamut of the input image is color-compressed to the color within the color gamut of the projection unit 100. The compression rate calculation circuit obtains (C ^* _in / C ^* _out ) as the compression rate α _in some C ^* _in .

  FIG. 24 is an explanatory diagram of a third modification of the present embodiment. FIG. 24 shows the saturation before color compression on the horizontal axis and the compression rate α on the vertical axis, the change (T20) in the compression rate α in the present embodiment, and the compression rate α in the third modification of the present embodiment. This is a comparison with the change (T21).

  As shown in FIG. 24, similarly to the change (T20) of the compression rate α in the present embodiment, the compression rate α in the third modification example of the present embodiment increases toward the higher saturation side (T21). On the other hand, also in the third modification of the present embodiment, the compression rate α changes so as to increase toward the high saturation side, although the manner of change is different. Therefore, even in the third modification of the present embodiment, even if the saturation gain is increased toward the higher saturation side and the detail portion is crushed by the color compression processing, the correction amount is increased accordingly, and the detail portion is changed. The appearance can be improved.

In the third modification of the present embodiment, the color compression circuit stores the information calculated by the compression ratio calculation circuit in, for example, the LUT format, and the saturation from the RGB → L ^* C ^* h ^* conversion circuit. Based on the signal C ^* , a saturation signal after color compression is output. That is, the LUT includes an input value C ^* _in and an output value C ^* _{out at} a plurality of sampling points on the saturation correction curve calculated by the compression ratio calculation circuit for each combination of the lightness signal L ^* and the hue signal h ^*. The compression rate α at each sampling point is stored. When the saturation signal C ^* from the RGB → L ^* C ^* h ^* conversion circuit is input, the color compression circuit outputs the lightness signal L ^* and hue signal from the RGB → L ^* C ^* h ^* conversion circuit 40. The saturation signal C ^* corresponding to the combination of h ^* is set as an input value C ^* _in , and an output value C ^* _out corresponding to this is output.

  According to the third modification of the present embodiment, only the saturation signal in a given spatial frequency band can be corrected according to the compression rate α at the time of color compression, as in the present embodiment or its modification. As a result, it is possible to improve the appearance of detail portions lost during color compression without affecting other portions. Furthermore, by extracting noise and emphasizing the detail portion according to the extracted noise amount, it is possible to improve the appearance of the detail portion lost during color compression without amplifying the noise.

4.4 Fourth Modification In this embodiment or its modification, a projector is described as an example of an image output apparatus. However, the present embodiment is not limited to this, and the image output apparatus is a printer. Also good.

  FIG. 25 is a block diagram illustrating a configuration example of a printer according to the fourth modification of the present embodiment. In FIG. 25, the same parts as those in FIG.

  The printer (image printing apparatus) 400 includes an image processing unit 30 and a printing unit 410 as an image output unit. The image processing unit 30 receives the color gamut data of the input image and the color gamut data of the printing unit 410. Then, the image processing unit 30 generates a saturation correction curve and a compression rate, performs color compression processing when input image data is input, and outputs the image data after color compression to the printing unit 410. . The printing unit 410 performs printing based on the image data from the image processing unit 30.

  The image processing unit 30 in the fourth modified example of the present embodiment can be replaced with any one of the first to third modified examples of the present embodiment.

  According to the fourth modified example of the present embodiment, only the saturation signal in a given spatial frequency band can be corrected according to the compression rate α at the time of color compression, as in the present embodiment or a modified example thereof. As a result, it is possible to improve the appearance of detail portions lost during color compression without affecting other portions. Furthermore, by extracting noise and emphasizing the detail portion according to the extracted noise amount, it is possible to improve the appearance of the detail portion lost during color compression without amplifying the noise.

  As described above, the image processing apparatus, the image output apparatus, the image processing method, and the program according to the present invention have been described based on the above-described embodiment or its modification. However, the present invention is limited to the above-described embodiment or its modification. However, the present invention can be implemented in various modes without departing from the gist thereof, and for example, the following modifications are possible.

  (1) In each of the above-described embodiments or modifications thereof, only the saturation component is the processing target in the color compression processing, but the present invention is not limited to this. For example, in the color compression process, in addition to the saturation component, at least one of the brightness component and the hue component corresponding to the saturation component may be processed.

  (2) In each of the above-described embodiments or modifications thereof, an example in which color compression processing is performed in the CIELAB color space has been described, but the present invention is not limited to this. For example, the present invention can be applied to a case where color compression processing is performed in the CIELV color space or other color spaces.

  (3) In each of the above-described embodiments or modifications thereof, the example in which the image processing unit outputs the pixel value after converting it into the RGB color system has been described, but the present invention is not limited to this. The image processing unit may convert the color system to a color system other than the RGB color system (for example, CMYK color system) and output the result.

  (4) In each of the above embodiments or modifications thereof, an example in which the saturation correction curve is represented by a quadratic function on the high saturation side has been described, but the present invention is not limited to this. For example, the saturation correction curve may be represented by a linear function on the high saturation side.

  (5) In each of the above-described embodiments or modifications thereof, the saturation signal is corrected by removing the saturation noise by the noise extraction / removal circuit 210. However, the present invention is not limited to this. is not. For example, a configuration in which the noise extraction / removal circuit 210 is omitted in FIG. 6 may be adopted, and saturation signal correction processing may be performed without removing saturation noise.

  (6) In each of the above embodiments or modifications thereof, the projector has been described as an example of the image display device, but the present invention is not limited to this. The image display device according to the present invention can be applied to all devices that perform image display, such as liquid crystal display devices, plasma display devices, and organic EL display devices.

  (7) In each of the above-described embodiments or modifications thereof, it has been described that a light valve using a transmissive liquid crystal panel is used as the light modulation element, but the present invention is not limited to this. For example, DLP (Digital Light Processing) (registered trademark), LCOS (Liquid Crystal On Silicon), or the like may be employed as the light modulation element.

  (8) In each of the above-described embodiments or modifications thereof, a light valve using a so-called three-plate transmission type liquid crystal panel as the light modulation element has been described as an example, but a single-plate type liquid crystal panel, two plates, or four You may employ | adopt the light valve using the transmissive liquid crystal panel more than a plate type.

  (9) In each of the above embodiments, one pixel is described as being composed of three color component sub-pixels, but the present invention is not limited to this. The number of color components constituting one pixel may be 2, or 4 or more.

  (10) Although the present invention has been described as an image processing apparatus, an image output apparatus, an image processing method, and a program in each of the above embodiments or modifications thereof, the present invention is not limited to this. For example, an image display system including the image processing apparatus or the image output apparatus described above may be used. Alternatively, for example, a program describing a processing method of an image processing apparatus (image processing method) for realizing the present invention or a processing procedure of an image display apparatus processing method (image display method) for realizing the present invention Alternatively, it may be a recording medium on which the program is recorded.

2 ... Input image data, 4 ... Image data, 6, 8 ... Color gamut data,
DESCRIPTION OF SYMBOLS 10 ... Image display system, 20 ... Projector, 30 ... Image processing part,
32 ... Input image color gamut data storage unit, 34 ... Display device color gamut data storage unit,
36: Compression ratio calculation circuit, 40: RGB → L ^* C ^* h ^* conversion circuit, 50 ... Color compression circuit,
60 ... Line memory, 70 ... L ^* C ^* h ^* → RGB conversion circuit, 100 ... Projection unit,
110: Light source 112, 114: Integrator lens 116: Polarization conversion element
118 ... Superimposing lens, 120R ... R dichroic mirror,
120G ... Dichroic mirror for G, 122,148,150 ... Reflective mirror,
124R ... R field lens, 124G ... G field lens,
130R ... R liquid crystal panel, 130G ... G liquid crystal panel,
130B ... Liquid crystal panel for B, 140 ... Relay optical system,
142, 144, 146 ... relay lens, 160 ... cross dichroic prism,
170 ... projection lens, 200 ... detail enhancement circuit,
210 ... noise extraction / removal circuit, 212 ... high frequency component extraction circuit,
214 ... HPF circuit, 220 ... Saturation noise elimination circuit, 222 ... LPF circuit,
224,252 ... weight calculating _{circuit, 226,227,254 1, 254 2, 254} 3, 258,304 1, 304 2, 304 3, M1 ... multiplier,
228, 256, 306, A1 ... adder, 230 ... multistage filter circuit,
232 ... First filter circuit, 234 ... Second filter circuit,
236 ... a third filter circuit,
250, 250a, 250b ... correction amount calculation circuit,
260 ... saturation gain calculation circuit, 270 ... correction circuit,
302 ₁ ... 1st LUT, 302 ₂ ... 2nd LUT, 302 ₃ ... 3rd LUT,
352 ... LUT, 400 ... printer, 410 ... printing unit, C1 ... color compression means,
L1 ... Signal extraction means, G1 ... Saturation gain generation means, SCR ... Screen

Claims (12)

An image processing device for correcting image data supplied to an image output device,
A color compression unit that compresses the saturation component of the image data at a compression rate corresponding to the combination of the lightness component and the hue component of the image data based on the color gamut of the input image and the color gamut of the image output device; ,
A correction amount calculation unit that calculates a correction amount of a saturation component of the image data according to the compression rate for image data in a given spatial frequency band;
Using the correction amount, seen including a correction unit for correcting the luminance component of the image data compressed by the color compression unit,
The correction amount calculation unit
An image processing apparatus that calculates the correction amount so that an amplification amount of the saturation component in a high frequency region is larger than that in a low frequency region in the spatial frequency band . In claim 1,
Based on the color gamut of the input image and the color gamut of the image output device, a compression rate calculation unit that calculates the compression rate of the saturation component of the image data according to the combination of the lightness component and the hue component of the image data Including
The color compression unit is
An image processing apparatus, wherein the saturation component of the image data is compressed with the compression rate calculated by the compression rate calculation unit. In claim 2,
The compression rate calculation unit
In the saturation correction curve indicating the relationship between the saturation component Cin before color compression and the saturation component Cout after color compression, calculating the reciprocal number ΔCin / ΔCout of the gradient in the saturation component Cin as the compression rate. A featured image processing apparatus. In claim 2,
The compression rate calculation unit
An image processing apparatus, wherein Cin / Cout is calculated as the compression rate in a saturation correction curve indicating a relationship between a saturation component Cin before color compression and a saturation component Cout after color compression. In any one of Claims 1 thru | or 4,
A saturation noise removing unit that removes a given saturation noise component from the saturation component;
The correction unit is
An image processing apparatus that corrects a saturation component of the image data from which the saturation noise component has been removed by the saturation noise removal unit, using the correction amount. In claim 5,
The correction amount calculation unit
The image processing apparatus, wherein the correction amount is calculated so that the amount of amplification of the saturation component increases as the amount of the saturation noise component removed by the saturation noise removal unit decreases. In any one of Claims 1 thru | or 6.
The correction amount calculation unit
An image processing apparatus that calculates the correction amount of the saturation component such that the amplification amount of the saturation component increases as the compression rate increases.   An image processing device for correcting image data supplied to an image output device,
  A color compression unit that compresses the saturation component of the image data at a compression rate corresponding to the combination of the lightness component and the hue component of the image data based on the color gamut of the input image and the color gamut of the image output device; ,
  A correction amount calculation unit that calculates a correction amount of a saturation component of the image data according to the compression rate for image data in a given spatial frequency band;
  A correction unit that corrects a saturation component of the image data compressed by the color compression unit using the correction amount;
  A saturation noise removing unit that removes a given saturation noise component from the saturation component;
  The correction unit is
  An image processing apparatus that corrects a saturation component of the image data from which the saturation noise component has been removed by the saturation noise removal unit, using the correction amount.   In claim 8,
  The correction amount calculation unit
  The image processing apparatus, wherein the correction amount is calculated so that the amount of amplification of the saturation component increases as the amount of the saturation noise component removed by the saturation noise removal unit decreases.   An image processing device for correcting image data supplied to an image output device,
  A color compression unit that compresses the saturation component of the image data at a compression rate corresponding to the combination of the lightness component and the hue component of the image data based on the color gamut of the input image and the color gamut of the image output device; ,
  A correction amount calculation unit that calculates a correction amount of a saturation component of the image data according to the compression rate for image data in a given spatial frequency band;
  A correction unit that corrects a saturation component of the image data compressed by the color compression unit using the correction amount;
  The correction amount calculation unit
  An image processing apparatus that calculates the correction amount of the saturation component such that the amplification amount of the saturation component increases as the compression rate increases. An image output device that outputs an image based on image data,
An image processing apparatus according to any one of claims 1 to 10 ,
And an image output unit that outputs an image based on the image data corrected by the image processing device. An image processing method for correcting image data supplied to an image output device,
A color compression step of compressing the saturation component of the image data at a compression rate corresponding to the combination of the lightness component and the hue component of the image data based on the color gamut of the input image and the color gamut of the image output device; ,
A saturation component correction amount calculating step for calculating a correction amount of a saturation component of the image data according to the compression rate for image data in a given spatial frequency band;
Using said correction amount, seen including a luminance component correcting step of correcting the luminance component of the image data compressed in the color compression step,
In the saturation component correction amount calculating step,
In the spatial frequency band, the correction amount is calculated so that the amount of amplification of the saturation component in the high frequency region is larger than that in the low frequency region .