JP2007181189A - Image processing device, display device, image processing method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing device, display device, image processing method and program in which desirable gradation-extending processing can be performed by more appropriately detecting a gradation region in an image region of smooth gradations while being hardly affected by a noise component. <P>SOLUTION: When detecting a linear interpolation application region by sequentially scanning a pixel stream of an inputted image digital signal, a detection unit judges that a gradation change is caused by a noise or the like when a gradation difference at a position next to the position where that gradation change has been detected, is identical to a gradation difference before the position where the gradation change has been detected, in the case where the gradation change in a predetermined range (for example, a minimum gradation difference) is detected, and assumes that the gradation difference of the pixels in which a gradation change has been detected is the gradation value of the preceding and following pixels. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image processing device, a display device, an image processing method, and a program that perform gradation expansion processing on an image signal.

  In recent years, display devices such as thin displays have been improved in resolution and multi-gradation in order to provide users with higher quality and realistic images. The image signal supplied to the display device is digitized, and generally 6 to 8 bit data is assigned to each pixel for each of R (red), G (green), and B (blue) color components. .

  When the number of bits that can be displayed by the display device is the same as the number of bits of the image signal, the display device basically displays the input signal as it is. However, in many cases, the number of bits that can be displayed on the display device is different from the number of bits of the input image signal. When the number of bits of an image signal is larger than the number of bits that can be displayed on the display device, the display device uses a method of truncating the lower bits of the image signal, a dither method, an FRC (frame rate control) method, or the like. Reduce the number of bits in the signal.

  On the other hand, when the number of bits of the image signal is smaller than the number of bits that can be displayed by the display device, the number of bits of the image signal is increased by adding lower bits (gradation expansion processing). This gradation expansion processing is also used when image signal data processing is executed in the display device in accordance with the characteristics of the display device. Further, the gradation expansion processing is executed to increase the calculation accuracy even when the number of bits that can be displayed on the display device is the same as the number of bits of the image signal. In this case, the image signal is converted into the number of bits that can be displayed on the display device using the dither method, FRC, or the like after the gradation expansion processing is executed.

  Further, the gradation expansion process is used in addition to the conversion of the number of bits of the digital signal and the improvement of calculation accuracy. For example, if the number of bits of the digital signal is small, in a region where the gradation changes smoothly like gradation, a false contour that appears in a contour line (originally, the gradation should change smoothly in the plane, The gradation change portion is not perceived as being smoothly changed and is recognized as having an outline). The gradation expansion process is also used as a technique for preventing this.

  Generally, gradation expansion processing is divided into two types: (1) a method for performing the same processing on all image signals, and (2) a method for extracting an image signal of a specific image and performing processing only on necessary pixels. .

  (1) As a method of performing the same processing on all image signals, firstly, a method of adding dither noise or random noise can be considered. Although this method can suppress the false contour to some extent, there is a problem that the added noise component is conspicuous.

  Second, there is a method of adding the value of the upper bit as the lower bit. For example, in order to change the 6-bit input signal “101101” to 8 bits, the upper 2 bits of the input signal are added to the lower 2 bits and converted to “10110110”. A third method is simply to add 0 or 1 to the lower bits. These second and third methods are simple, but the false contour cannot be suppressed because the gradation difference does not become small at the gradation changing portion.

  On the other hand, (2) as a method for extracting an image signal of a specific image and performing processing only on necessary pixels, firstly, it is described in Japanese Patent Laid-Open No. 63-15576 (hereinafter referred to as Patent Document 1). There is a method of applying a low-pass filter (LPF) process to the false contour region. In this prior art, in order to suppress the false contour generated by performing gamma correction (image processing) on the digital image signal, an area where the false contour is generated is adaptively determined, and neighboring pixels in the area are determined. The integrated value of the image signal (synonymous with LPF processing) is output. By this LPF processing, the gradation difference in the area where the false contour is generated is reduced.

  However, according to this method, when the false contour generation interval (that is, the contour line interval) is larger than the filter size (the integration range of neighboring pixels), the distinction between the portion subjected to the filtering process in the gradation region and the portion other than that is not performed. Suppressing false contours does not lead to much improvement in image quality.

  Therefore, as a second method, in order to suppress false contours generated by performing gamma correction (image processing) described in JP-A-4-165874 (hereinafter referred to as Patent Document 2), When a region (gradation region) in which a change in tone is gentle is determined, a gradation value of a pixel between contour lines of a false contour in the region is obtained by linearly interpolating a gradation value of a pixel on the contour line. is there. According to this method, a uniform gradation change can be realized in the gradation area, and thus the problem as in the first method does not occur.

  From the above, it is considered that a method of detecting specific information of pixels and performing linear interpolation according to the detection result is more preferable as a gradation expansion processing method from the viewpoint of suppressing false contours. Methods using this linear interpolation are disclosed in Japanese Patent Application Laid-Open No. 2003-304400 (hereinafter referred to as Patent Document 3), Japanese Patent Application Laid-Open No. 2003-333348 (hereinafter referred to as Patent Document 4) and Japanese Patent Application Laid-Open No. 2004-54210 ( (Hereinafter referred to as Patent Document 5).

  In Patent Documents 3 to 5, unlike Patent Documents 1 and 2, in order to solve the problem of false contours due to the shallow bit depth of the digital image signal, or to maximize the gradation performance of the display device However, the method of linear interpolation is the same as in Patent Document 1 and Patent Document 2.

  The image processing apparatus described in Patent Document 3 has a configuration including a false contour detector and a pixel value converter. In this false contour detector, the same luminance level continues for two or more pixels in the horizontal direction, and then the luminance level increases by 1 (condition 1). The case of continuing in the direction (condition 2) is set as a false contour detection condition. Then, linear interpolation is performed on the detected false contour by a pixel value converter.

  The color signal expansion device described in Patent Document 4 has a configuration including a data distribution detection unit and a data depth expansion unit. The data distribution detection unit extracts (detects) a region in which the color changes gently from the distribution state of the gradation data. Specifically, in the pixel group K in which the same gradation continues, the number of pixels is not less than the lower limit threshold P and not more than the upper limit threshold Q, and the gradation difference with the pixels of the adjacent pixel group is not more than the determination threshold S. Detect areas. Then, the data distribution detection unit performs linear interpolation on the gently changing region, and determines a gradation value to be added to the region. The data depth extension unit generates extension image data in which the data depth of the color signal is extended while adding the gradation value to the extension part.

The image processing apparatus described in Patent Document 5 is configured to include a detection unit and a signal expansion unit. The detection means determines whether the difference between the first position where the same pixel data continues and the first position where the next pixel data continues is equal to the width where the same pixel data continues, and further the same pixel data The presence or absence of a pseudo (false) contour is determined by determining whether the gradation value of the area where the pixel values are continuous is one larger or one smaller than the gradation value of the area where the next pixel data is continuous. Then, the image expansion is performed on the image data smoothly and linearly (by performing linear interpolation) so that a smooth continuous image can be obtained in the region where the pseudo contour is generated.
JP-A 63-15576 JP-A-4-165874 JP 2003-304400 A JP 2003-333348 A JP 200454210 A

  Among the conventional image processing apparatuses described above, the configurations disclosed in Patent Documents 3 to 5 are not problematic in that gradation expansion processing by linear interpolation as described in Patent Document 2 is performed. However, when detecting a linear interpolation application region for performing gradation expansion processing by linear interpolation, a condition that regions where the same gradation is continuous is adjacent and the gradation difference between the regions is within a certain value. Therefore, there is a problem in that it is easily affected by noise components, and appropriate detection cannot be performed, and desirable gradation expansion processing cannot be performed.

  The present invention has been made to solve the above-described problems of the prior art. In a gentle gradation image area, the present invention is less susceptible to noise components and detects the gradation area more appropriately. An object of the present invention is to provide an image processing device, a display device, an image processing method, and a program capable of performing desirable gradation expansion processing.

  In order to achieve the above object, according to the present invention, when the linear interpolation application region is detected, if the gradation values of the pixels before and after the pixel in which the gradation change within the predetermined range is detected are the same, the gradation It is determined that the change is due to noise or the like, and the tone value of the pixel in which the tone change is detected is regarded as the tone value of the previous and subsequent pixels.

  Therefore, it is possible to appropriately detect a false contour region of an image containing a large amount of noise and error components, which has been difficult to detect in the past, and thus it is possible to perform more desirable high-quality gradation expansion.

  In addition, when the gradation expansion process is performed on a region including noise / error components, the noise components can be suppressed, so that a high-quality display can be obtained.

  According to the present invention, it is difficult to be affected by a noise component, and a gradation area can be detected more appropriately and gradation expansion processing can be performed appropriately.

  First, the principle of the present invention will be described before describing the present invention.

(Principle of the invention)
In the conventional gradation expansion processing, a region where a false contour is generated or a region where gradation variation should be smoothed by performing gradation expansion processing by linear interpolation (hereinafter referred to as a linear interpolation application region) is detected. As a method, a detection condition is used in which areas that are continuous with pixels having the same gradation value are adjacent to each other, and the difference in gradation value between the areas is within a certain range. Such a detection method is applied to linear interpolation when the gradation is monotonously increasing or decreasing in a region to be detected, such as a gradation artificially formed by CG (computer graphics). The area can be detected without problems. However, when an image signal containing additional noise such as dither noise or high-frequency noise such as JPEG is input, it is easily influenced by noise components, and a completely different gradation expansion processing result is output. Such problems of the prior art will be specifically described with reference to FIGS.

  FIG. 1A shows an example of a 6-bit image signal having no noise component to be processed, and FIG. 1B shows the detection result of the linear interpolation application region by the conventional gradation expansion processing. c) shows a result of gradation expansion processing (that is, 2 bits to be added are generated) to 8 bits. 1A to 1C, the horizontal axis indicates the pixel position x, the vertical axis in FIG. 1 indicates the gradation value f (x), and the gradation value of each pixel is indicated by a rectangle. .

  In FIG. 1A, the 6-bit image signal to be processed is that f (0) to f (7) are (001100) bin ((XXXXXXX) bin represents a binary number), and f (8) To f (15) are (001101) bins, f (16) to f (23) are (001110) bins, and f (24) and f (25) are (001111) bins.

  Thus, since the gradation value f (x) changes smoothly as the pixel position x changes, it is considered that this pixel column expresses gradation. In such a gradation image, it is desirable that the gradation changes more smoothly.

  When the 6-bit image signal shown in FIG. 1A is converted into an 8-bit image signal, the contour and the linear interpolation application area are first detected.

  In the contour detection process and the linear interpolation application area detection process, first, x = 0 is held as the value of the start point Xs, and the tone value f (0) = (001100) bin of the start point is held as the start point tone value Ts. . Next, a minimum position x that is larger than Xs and satisfies f (x) ≠ Ts is detected. In this example, since f (8) = (001101) bin ≠ Ts and Xs <8, x = 8 is set as the detection point. Further, the gradation difference between f (8) and f (0) is 1 (minimum gradation difference), which is considered to be a linear interpolation application region. Hereinafter, the same processing as described above is sequentially executed with the detection point as the start point and the gradation value of the detection point as the start point gradation value. The result is shown in FIG. In this example, x = 8, 16, and 24 are obtained as detection points including x = 0. In this case, the gradation difference at all the detection points is 1, and the same gradation value is continuous between the detection points, so that at least pixel rows from x = 0 to 24 are linearly interpolated. It is considered as an application area.

  Next, a 2-bit gradation expansion process is performed on the image signal based on the detection result.

  In the gradation expansion processing, interpolation processing is performed on the pixel columns (pixel columns from x = 0 to 24) regarded as the linear interpolation application region in FIG.

  In the interpolation processing, first, the gradation values between the detection points are connected with straight lines (oblique dotted lines in FIG. 1C). Subsequently, a 2-bit value to be added to the gradation value that is closest to the straight line is determined. For example, in the region from x = 0 to 8, assuming that the start point of the straight line is the start point position Xs and the end point of the straight line is the end point position Xe, the added 2-bit value is (additional value) = (x−Xs) / (Xe−Xs) * 4 = (x−0) / (8−0) * 4 can be obtained (the fractional part is rounded down). Note that “*” in the above expression means multiplication.

  Here, “4” is obtained as a power of 2 (the number of bits to be added). According to the above formula, the added value is (00) bin for x = 0, 1; (01) bin for x = 2, 3; (10) bin for x = 4, 5; (11 for x = 6, 7; ) Bin. By adding this value as lower bits to 6-bit pixel data (gradation value), 8-bit extended correction data can be obtained. Note that (00) bin is added to pixel data of x = 25 not included in the linear interpolation application region.

  Looking at the processing result of FIG. 1 (c), the gradation difference between the detection point and the detection point changes in four steps by extending the pixel data to 8 bits, and the gradation changes smoothly. I understand.

  On the other hand, an example in which a noise component is included in an image signal is shown in FIG. In the image signal shown in FIG. 2A, the gradation value of x = 3 is changed from (001100) bin to (001101) bin, and the gradation value of x = 19 is changed from (001100) bin to (001101) bin. This is different from the image signal shown in FIG. These two gradation values are noise components. In this way, the change of the gradation value also affects the detection of the linear interpolation application region.

  FIG. 2B shows the detection results of the contour and the linear interpolation application region.

Similarly to the processing result for the image signal shown in FIG. 1B, x = 0 is held as the value of the start point Xs, and the tone value f (0) = (001100) bin of the start point is held as the start point tone value Ts. To do.
In this example, the first f (x) ≠ Ts is x = 3. Hereinafter, the same processing is sequentially performed with the detection point as the start point and the detection point gradation value as the start point gradation value. The result is shown in FIG. In this example, x = 3, 4, 8, 16, 19, 20, and 24 are obtained as detection points including x = 0.

  Next, a linear interpolation application region is determined based on the detection result. Here, as conditions for the linear interpolation application region, (1) the same gradation value as the start point position is continuous for a plurality of pixels and the same gradation value as the end point position is continuous for a plurality of pixels, and (2) the gradation at the start point position The change is a decrease and the tone change to be smoothed, or the tone change at the end point position is an increase and the tone change to be smooth, specifically, the tone value at the start point position The difference between the gradation values at the end point position and the end point position is the minimum gradation difference (for example, the gradation difference is 1). (3) When the start point position is other than x = 0, the gradation change at the start point position and the end point position A case will be described as an example in which three points are used in which the gradation change is both increased or decreased. There are several possible variations for the detection conditions, but the purpose of determining the area for linear interpolation in order to change the gradation smoothly is the same.

  The above (1) is a condition that it is not necessary to smooth the gradation change in the region where the gradation is changed for each pixel, and the above (2) is a normal outline or a smooth gradation change. The above condition (3) for determining whether the contour should be a false contour is a condition for determining an area in which interpolation processing for simply increasing or decreasing the gradation in the area is executed. The gradation data shown in FIG. 1 satisfies the conditions (1) to (3) from the pixel position x = 0 to 24.

  Under the above conditions, as shown in FIG. 2B, each pixel data is determined in order from x = 0.

  When Xs = 0 and Xe = 3, the condition (1) is not satisfied at these positions ((the same gradation value as the gradation value of Xe = 3 is not continuously plural), so it is determined as the linear interpolation application region. Not.

  When Xs = 3 and Xe = 4, the condition (1) is not satisfied at these positions in the same manner as described above.

  When Xs = 4 and Xe = 8, the tone change at the start point position decreases at these positions, and the tone change at the end point position increases, so the condition (3) is not satisfied.

  When Xs = 8 and Xe = 16, all the conditions are satisfied at these positions, so that a linear interpolation region is obtained. Hereinafter, when the determination is made sequentially, it can be seen that even when Xs = 20 and Xe = 24, the linear interpolation application region is obtained.

  FIG. 2C shows the result of performing linear interpolation processing on the pixel positions x = 8 to 16 and x = 20 to 24. The processing method is the same as the method described with reference to FIG. As shown in FIG. 2C, the result of linear interpolation processing is the same as in FIG. 1C in the region from x = 8 to 16 that is not affected by the noise generated at the positions x = 3 and x = 19. It has become. On the other hand, in a region including x = 3 and x = 19, a processing result different from that in FIG. 1C is obtained.

  Thus, in the example shown in FIG. 1, since there is no noise component in the image signal, a smooth gradation change is obtained in all regions (positions) by the gradation expansion process. On the other hand, in the example shown in FIG. 2, since a gradation change due to a noise component is regarded as a detection point and detected as a start point or an end point of linear interpolation, a processing result completely different from that in FIG. 1C is obtained. Note that some of the above-described conventional techniques may not detect, but even in that case, the start point and end point of the linear interpolation application region are reset, and thus the same processing result as in FIG. 1C cannot be obtained. This suggests that the conventional gradation expansion processing is affected even by a slight gradation change that is hardly perceived when an image is viewed, such as a gradation difference of one pixel per pixel.

  For such a slight gradation change, it is desirable that the detection process of the linear interpolation application area in the gradation expansion process does not affect the interpolation process. The reason is due to the main generation factor of the gradation change.

  In general, when a natural image is displayed on a display device, the image data is irreversibly compressed by JPEG or MPEG format in order to reduce the file capacity. In addition, the gradation expression is expanded by adding dither noise to an image in which the number of gradations is limited. What is common to these processed images is that the noise (error) component is included as a high-frequency component, taking advantage of the fact that the sensitivity of the human eye is higher in the low-frequency component than in the high-frequency component. It is. Such processing makes the noise (error) component relatively inconspicuous. In general, it is considered that the amplitude of the noise / error component is sufficiently smaller than that of the main component.

  For example, when the gradation value is 6 bits (0 to 63), the gradation value 23 and the gradation value 24 are alternately displayed in the dither method, thereby realizing a halftone of 23.5 gradations. In this case, the change from the gradation value 23 to the gradation value 24 and the change from the gradation value 24 to the gradation value 23 should not be detected as false contours or normal contours. The same applies to high-frequency errors due to lossy compression processing such as JPEG and MPEG.

  Therefore, a signal component that is a high-frequency component and has a small amplitude, specifically, a change in one gradation per pixel is often a signal expressing a halftone or simply an irreversible compression / decompression error. It is desirable not to detect the gradation change occurring for this reason as the linear interpolation application area at the time of gradation expansion.

  FIG. 3A shows an example of a 6-bit image signal to be processed, and FIG. 3B shows a linear interpolation application region by gradation extension processing when a change in one gradation per pixel is ignored. FIG. 3C shows the detection result, and FIG. 3C shows the result of gradation expansion processing (that is, generating 2 bits to be added) to 8 bits.

The image signal shown in FIG. 3 (a) is the same image signal as in FIG. 2 (a), and FIG. 3 (b) shows the result of performing detection processing of the linear interpolation application region on the image signal. In FIG. 3B, since the change of 1 gradation per pixel is not detected, the detection points are only x = 0, 8, 16, and 24. This is the same as the detection processing result shown in FIG. 1B, and the linear interpolation application region is also changed from x = 0 to 24.
In the process shown in FIG. 3B, the detection condition (1) for the linear interpolation application region described above is “a plurality of pixels having the same gradation value as the start point position and a plurality of pixels having the same gradation value as the end point position. However, it is only necessary to change that “the change of one gradation per pixel is regarded as the same gradation continuing”.

  Therefore, when linear interpolation processing is performed based on the detection result of FIG. 3B, the processing result shown in FIG. 3C is obtained. In FIG. 3C, the same processing result as in FIG. 1C is obtained at pixel positions other than x = 3 and 19.

  At pixel positions x = 3 and 19, which are noise / error components, the result of the linear interpolation process may be used as it is, but here, the result of the linear interpolation process and the average value of the input gradation values are output. In this way, it can be seen that a processing result equivalent to that shown in FIG.

  Up to this point, it has been described by taking an example of a change in one gradation of one pixel as a signal component having a high frequency component and a small amplitude, assuming that the same gradation is continuous. However, depending on the image, there may be a change in one gradation of two pixels or one gradation of three pixels in order to express a halftone or as an error in non-decompression / decompression / decompression. For example, an image obtained by simply enlarging the original image twice or three times corresponds to this example. In such an image, the change of 1 gradation per pixel of the original image becomes the change of 1 gradation of 2 pixels or 1 gradation of 3 pixels. Are not considered to be continuous.

  Further, when the definition of the display device is high, not only the gradation of one pixel but also the change of one gradation of two pixels or one gradation of three pixels may be easily perceived as an error. Even in such a case, the above condition “change in one gradation per pixel is regarded as the same gradation is continuous” does not apply.

  FIG. 4 shows an example in which a linear interpolation process is performed without detecting a change in gradation of two pixels when a double enlarged image is input. FIG. 4A shows an example of an image signal enlarged twice, and gradation change occurs only in units of two pixels or more. Such a simply enlarged image is desirably subjected to the same gradation expansion processing as that in FIG. Therefore, in the present invention, the condition (1) for the linear interpolation application region is that “the same gradation value as the start point position is continuous for a plurality of pixels, and the same gradation value as the end point position is continuous for a plurality of pixels, provided that one pixel group “Change of one gradation is regarded as the same gradation is continuous”. Here, the “pixel group” refers to a group of a plurality of pixels having the same gradation value. When the original image is simply enlarged, all the pixels in the pixel group have the same gradation value. Here, since the original image is enlarged twice, 2 pixels × 2 pixels form one pixel group.

  FIG. 4B shows the detection processing result when the detection condition (1) for the linear interpolation application region is changed in this way. Here, the detection process is performed in units of two pixels such as x = 0, 2, 4,. By doing so, it is possible to detect a change in one gradation of one pixel group. In FIG. 4B, since the change of one gradation of one pixel group is not detected, the detection points are only x = 0, 8, 16, 24. When linear interpolation processing is performed based on this detection result, the processing result shown in FIG. 4C is obtained. Here, at the pixel positions x = 2, 3, 20, and 21, which are noise / error components, the result of the linear interpolation process and the average value of the input gradation values are output. Although the example in which the detection process is performed in units of two pixels has been shown, the same effect can be obtained by performing a process of “detection process for each pixel and ignoring the change of n gradation for one pixel”. .

  From the above, the present invention comprises the following components as means for expanding the gradation of a digital image signal.

  (1) A detection unit for detecting a linear interpolation application region and an expansion correction unit that performs gradation expansion based on the detection result.

  (2) The detection unit sequentially scans the pixel row of the digital video signal and detects a gradation change. However, the gradation value within the predetermined range is detected, and the gradation value of the pixel next to the position where the gradation change is detected is the same as the gradation value of the pixel before the position where the gradation change is detected. If they are the same, no detection is performed, and gradation changes other than the above-described gradation changes are detected separately for detection points to which linear interpolation processing is performed and other detection points.

  (3) The expansion correction unit realizes appropriate gradation expansion processing by performing linear interpolation processing on the detection point on which the linear interpolation processing is performed.

  By applying the present invention to the following apparatus, method, and program, it is possible to realize gradation expansion processing that is resistant to noise and error and that can prevent false contours.

  For example, an image processing apparatus detects a linear interpolation application region of image data by the above-described detection method, and executes gradation expansion processing based on the detection result, thereby being resistant to noise and error and generating false contours. The image can be displayed with good image quality.

  The apparatus that executes the detection process and the gradation expansion process may be configured by a hardware circuit such as an LSI including a logic circuit or a memory, and can also be realized by an information processing apparatus such as a computer that executes a process according to a program. . In this case, the detection process may be performed by a hardware circuit (image detection device), and the gradation expansion process may be performed according to a gradation expansion program. The configuration may be such that the extension processing is executed by a hardware circuit (gradation extension processing device).

  The present invention can also be realized as an image processing method, an image processing program, an image detection apparatus that executes only detection processing, an image detection method, and an image detection program. Also, a high-quality image can be displayed by executing the above processing on the image data on the display device.

  Note that the gradation expansion processing is not limited to the method shown in FIGS. 3 and 4, and other processing may be used. For example, as shown in FIGS. 5 (a) to 5 (c), points where the difference in gradation value at the detection point is halved are connected (oblique dotted line in FIG. 5 (c)), and this straight line is connected. A method of determining the bits to be added so as to be the closest value is also possible. FIG. 5A is the same as FIG. 3A showing the 6-bit image data to be processed, and the detection result of the linear interpolation application region shown in FIG. 5B is the same as FIG. 3B. It is.

  Further, other arbitrary interpolation functions can be used instead of the so-called linear interpolation processing. In the present invention, by executing the gradation change suppression process, it is possible to perform a gradation expansion process that can suppress the occurrence of false contours at low cost regardless of the type of interpolation process.

  Hereinafter, an embodiment of the present invention based on the principle described above will be described.

(First embodiment)
FIG. 6 is a block diagram showing the configuration of the image processing apparatus according to the first embodiment of the present invention. The image processing apparatus shown in FIG. 6 is a specific apparatus that executes the processing of the present invention based on the principle shown in FIGS.

  As shown in FIG. 6, the image processing apparatus according to the first embodiment is configured to include a detection unit 11, a line buffer 13, and an extended correction unit 12. The image processing apparatus according to the first embodiment sequentially receives 6-bit image data, converts the 6-bit image data into 8-bit image data, and outputs the converted image data to a display device or the like.

  The detection unit 11 sequentially scans the input 6-bit image data for each column, performs gradation expansion processing by linear interpolation for each column, and detects a linear interpolation application region that smoothly changes the gradation.

  When detecting the gradation change within a predetermined range (for example, the minimum gradation difference) when sequentially scanning the input image data for each column, the detection unit 11 detects the gradation change. If the tone value at the next position is the same as the tone value at the previous position, it is determined that the tone change is noise or the like, and the tone value of the pixel where the tone change is detected is determined. It is regarded as the gradation value of the pixel at the position before and after the pixel.

  The line buffer 13 accumulates the input 6-bit image data while the detection unit 11 performs the detection process.

  The expansion correction unit 12 performs gradation expansion processing on the image data output from the line buffer 13 using the detection point position data X obtained by the detection unit 11 and the gradation change amount FC of the detection point. Do. In the image processing apparatus according to this embodiment, the line buffer 13 is provided so that extended correction based on the detection result is performed at an appropriate position in the image.

  6 shows a configuration corresponding to one of the RGB color components, the image processing apparatus of the present embodiment has the same configuration in parallel for the other two colors. The same applies to other embodiments.

  Next, the image processing apparatus of this embodiment will be described separately for the detection unit 11 and the extended correction unit 12.

  First, a specific configuration and operation of the detection unit 11 will be described with reference to FIGS. 7 and 8.

  FIG. 7 is a block diagram illustrating an example of the configuration of the detection unit illustrated in FIG. 6, and FIG. 8 is a graph illustrating a process when an arbitrary pixel column is input to the detection unit illustrated in FIG. 5. .

  As shown in FIG. 7, the detection unit 11 has a configuration including a determination output unit 21, a starting point parameter holding unit 22, and a counter 23. The counter 23 is used to relatively grasp what position the sequentially input image data is. If the position of the input image data is known, the counter 23 need not be provided. The start point parameter holding unit 22 holds the start point position Xs, the start point gradation Ts, and the start point gradation change amount FCs, which are parameters necessary for the determination process of the determination output unit 21. When a new detection point is obtained by the determination output unit 21, the parameter is changed.

  The gradation change amount FC indicates whether the detected gradation change is an increase direction gradation change or a decrease direction gradation change, and the gradation change should be subjected to linear interpolation processing. This is information indicating whether it is a change or a contour part that should not be subjected to linear interpolation processing.

  Specifically, the gradation change amount FC has the following value.

FC = 00: Gradation change to be subjected to linear interpolation processing, gradation change is increasing direction FC = 01 ... Gradation change to be subjected to linear interpolation processing, gradation change is decreasing direction FC = 10... Contour portion that should not be subjected to linear interpolation processing The determination output unit 21 receives the input image data T (x) (where x represents the position of the sequentially input image, and T (x) represents the position. x represents the gradation value), and the following determination is made based on the parameters held in the start point parameter holding unit 22 and the preset threshold value TH.

  (1) T (x) = Ts (when the start point gradation and the gradation of the input image are the same) or (Ts−TH <T (x) <Ts + TH and T (x + 1) = Ts) (change in gradation of the input image Is within the range of the start point gradation ± threshold and the start point gradation is the same as the gradation at the position x + 1: this corresponds to the noise / error component removal processing in the present invention). The gradation change is not used as a detection point (no processing is performed. The output is not changed).

  (2) The condition of (1) is not satisfied, and Ts−TH <T (x) <Ts + TH and T (x + 1) = T (x) (the gradation change of the input image is within the range of the start point gradation ± threshold value) And the gradation at the position x + 1 and the position x have the same value), this gradation change is set as a linear interpolation application region to which linear interpolation processing is performed. At this time, the output position X = x and the output gradation change amount FC are FC = 00 when Ts <T (x), and FC = 01 when Ts> T (x). In addition, the parameters held in the start point parameter holding unit 22 are changed to Xs, x, Ts, T (x), and FCs, respectively, and used in subsequent processing.

  (3) When the condition of (2) is not satisfied, this gradation change is set as a contour region. At this time, the output position X = x and the output gradation change amount FC = 10. Similarly to (2), the parameters held in the start point parameter holding unit 22 are changed in Xs to x, Ts to T (x), and FCs to FC, respectively, and used in subsequent processing.

  As described above, the detection unit 11 sequentially scans the pixel row of the image signal, ignores the gradation change of one gradation per pixel, does not detect it, and detects other gradation changes as a target of linear interpolation processing. Are detected separately from other detection points.

  Note that the threshold value TH is a reference value for determining whether the gradation change at the detection point is smoothed by correction or retained. The threshold TH may be set to an appropriate value based on the contents of processing, the characteristics of the input image, and the like. The simplest value is TH = 2 which smoothes the gradation change only by the minimum gradation difference. If the minimum gradation difference of the input image (for example, one screen) is 2, it is determined that the area having the minimum gradation difference is an area where gradation change is desired to be smoothed, and TH = 3. Is possible.

  The above processing will be confirmed by taking as an example a case where a pixel column as shown in FIG. Here, it is assumed that the threshold value TH = 2 and the image signals are sequentially input from x = 0.

  First, an initial condition indicating that no parameters are held is set in the start point parameter holding unit 22. For example, when a gradation value T (0) = (001100) bin at x = 0 is input, Xs = 0, Ts = T (0), and FCs = 10 are held. Here, FCs = 10 is because the presence or absence of gradation change cannot be determined when x = 0 (because there is no data x = −1).

  When the start point parameter is set, the detection output detection process is executed by the determination output unit 21 from x = 1. Here, since T (1) = Ts, the process proceeds to the process for the next pixel value T (2) without executing the detection process.

  When x = 4, T (4) ≠ Ts, Ts−TH <T (4) <Ts + TH is satisfied, and T (5) = Ts. Therefore, detection is not performed to satisfy the condition (1).

  Furthermore, when x = 8, Ts−TH <T (8) <Ts + TH and T (9) = T (8) are satisfied for the first time, and the condition (2) is satisfied. Therefore, X = 8 and FC = 00 are output, and the start point parameters are updated to Xs = 8, Ts = (001101) bin, and FCs = 00. From x = 9, detection processing is performed using the updated parameters.

  FIG. 8C shows the result of repeatedly executing the above processing (FIG. 8B) and performing the detection processing to the end. In FIG. 8C, arrows are attached to the detection points, black arrows are detection points to which linear interpolation processing is performed, and white arrows are other detection points. When the gradation change amount FC is 00 or 01, the extended correction unit 12 determines that the detection point is a detection point to be subjected to linear interpolation processing, and when the gradation change amount FC is 10, the detection point is detected. It is determined that the point is a detection point that should not be subjected to linear interpolation processing. In the example shown in FIG. 8C, it can be seen that the region from x = 0 to 15 is the target of linear interpolation processing. This region is determined as a region in which linear interpolation processing is not performed due to noise / error components of one gradation per pixel in the prior art.

  Next, the configuration and operation of the extended correction unit 12 will be described with reference to FIGS. 9 and 10.

  FIG. 9 is a block diagram illustrating a configuration example of the extended correction unit illustrated in FIG. 6, and FIG. 10 is a graph illustrating a result of the gradation expansion process when an arbitrary pixel column is input to the extended correction unit. .

  As illustrated in FIG. 9, the extended correction unit 12 includes a correction processing unit 24, an averaging correction unit 25, a parameter extraction unit 26, and a parameter buffer 27.

  The parameter buffer 27 accumulates the detection position X and the gradation change amount FC obtained by the detection unit 11 for each column (line) of the image. The parameter extraction unit 26 acquires, from the parameter buffer 27, Xs and Xe that satisfy Xs <x <Xe, and their change amounts FCs and FCe, according to the pixel position x of the image input to the correction processing unit 24.

  The correction processing unit 24 receives the image signal T (x) delayed by the pipeline by the line buffer 13, and performs gradation expansion based on the input value and Xs, Xe, FCs, and FCe acquired from the parameter extraction unit 26. The processing is performed, and the processing result Tout ′ (x) and the input signal T (x) are output. In the gradation expansion process, one of the following five processes is selected and executed according to the values of FCs and FCe.

(1) When FCs = 00 and FCe = 01 Tout ′ (x) = 4 * [T (Xs) − (T (Xe) −T (Xs)) / 2 * {1-abs (x * 2-Xs -Xe) / (Xe-Xs)}]
(2) When the condition of (1) is not satisfied and FCs = 01 and FCe = 00 Tout ′ (x) = 4 * [T (Xe) − (T (Xe) −T (Xs)) / 2 * { 1-abs (x * 2-Xs-Xe) / (Xe-Xs)}]
(3) When the condition of (2) is not satisfied, and FCs ≠ 01 and FCe = 00, Tout ′ (x) = 4 * [T (Xs) + (T (Xe) −T (Xs)) * (x− Xs) / (Xe-Xs)]
(4) When the condition of (3) is not satisfied and FCs = 01 and FCe ≠ 00, Tout ′ (x) = 4 * [T (Xs−1) + (T (Xs) −T (Xs−1)) * (X-Xs) / (Xe-Xs)]
(5) When the above conditions (1) to (4) are not satisfied Tout ′ (x) = 4 * T (x)
And

  The decimal part is rounded down. The above (1) to (4) are the linear interpolation processing, (1) and (2) are the linear interpolation processing of the convex portion and the concave portion, and (3) and (4) are the linear interpolation processing similar to the conventional example. . Further, (5) is a process for adding a fixed gradation value, and is used for detection points that are not subjected to linear interpolation processing.

  In the first embodiment, the above correction processing is used. However, the present invention is not limited to this. For example, only (3) and (4) may be used. The effect of can be obtained.

  Tout ′ (x) obtained by the correction processing unit 24 is 8 bits, and the data and T (x) and T (Xs) are sent to the averaging correction unit 25. The averaging correction unit 25 satisfies this equation when T (x) ≠ T (Xs) (x = 4, 6, and 11 in FIG. 8B). ), And outputs the average value of the result of linear interpolation and the input gradation value (Tout (x) = (4 * T (x) + Tout ′ (x)) / 2), otherwise Tout (x ) = Tout ′ (x) is output.

  The averaging correction unit 25 receives the digital image signal T (x) and the image signal Tout ′ (x) output from the correction processing unit 24, and performs correction processing output from the correction processing unit 24. The average value of the received image signal Tout ′ (x) and the digital image signal T (x) is calculated, and the gradation value T (x) of the input digital image signal is the starting point gradation T (Xs ), The average value is output. Otherwise, the output image signal Tout ′ (x) from the correction processing unit 24 is output as it is.

  The above processing is confirmed for the pixel column from which the detection result as shown in FIG. FIG. 10 (a) is a reproduction of FIG. 8 (c). An arrow is given to the detection position at that time, and the value of the gradation change amount FC is described above the arrow.

  Similarly to the detection process, the correction process is sequentially performed on the image data input from x = 0.

  In the region where x = 0 to x = 7, Xs = 0, FCs = 10, Xe = 8, and FCe = 00 (Xs <x <Xe), so the correction process (linear interpolation process) in (3) is performed. Applied. Similarly, the correction process (3) is applied to the region x = 8 to 14, and the correction process (4) is applied to the region x = 21 to 23 (FIG. 10B). A region indicated by a dotted line in FIG. 10B is a linear interpolation processing region.

  FIG. 10C shows a result of processing performed by the averaging correction unit 25 after the gradation expansion is performed by the correction processing unit 24. As shown in FIG. 10C, in the region where x = 0 to 15 where the minimum gradation difference is often observed, the gradation difference is smooth without being affected by the change in the gradation of each pixel. I understand that.

  As described above, the image processing apparatus according to the present embodiment includes the detection unit 11 for detecting the linear interpolation application region, and the extended correction unit 12 that performs gradation expansion based on the detection result. The pixel sequence of the input digital video signal is sequentially scanned to detect a gradation change. At that time, the gradation value within the predetermined range is detected, and the gradation value of the pixel next to the position where the gradation change is detected is the gradation value of the pixel before the position where the gradation change is detected. In the same case, the detection is not performed, and the gradation change other than the gradation change described above is detected separately for the detection point to which the linear interpolation process is applied and the other detection points. An appropriate gradation expansion process is realized by performing the linear interpolation process by the expansion correction unit 12 on the detection point on which the linear interpolation process is performed.

  Further, by outputting the result of linear interpolation processing and the average value of the input gradation values by the averaging correction unit 25, the amount of change of the signal estimated as a noise / error component is reduced, and the noise / error component is suppressed. it can.

  In the present embodiment, the detection unit 11 determines the detection position data and the gradation change amount FC of the detection position, and the correction processing is performed by the extended correction unit 12 based on the data. The processing executed by the unit 12 may be distributed in any way. For example, the detection unit 11 executes correction bit generation processing (a value obtained by subtracting the input image gradation from the processing result performed by the correction processing unit 12 in this embodiment), and only the gradation addition processing is performed by the extended correction unit 12. May be executed. Similarly, the processes of the correction processing unit 12 and the gradation change suppression unit 14 may be distributed and executed in any manner.

  In the present embodiment, an example in which the detection process is executed only in one direction (time-series arrangement direction of the image data of the input image: the X direction) is shown. For example, as the line buffer 13 illustrated in FIG. If an image data capable of storing a plurality of lines of image data is used, it is possible to perform not only X-direction detection / tone expansion processing but also Y-direction detection / tone expansion processing.

  However, since detection / gradation expansion processing in the Y direction depends on the number of lines that can be stored in the line buffer 13, detection / gradation expansion processing similar to that in the X direction cannot be performed in many cases. Therefore, in the Y-direction gradation expansion processing, a configuration is considered in which a noise / error component is removed by detecting a region where a gradation change is to be smoothed and passing the pixel data of the region through an LPF (low-pass filter). In this way, if the gradation expansion process in the X direction and the Y direction is appropriately changed according to the buffer constraint conditions and the like, the optimum gradation expansion process can be realized even with a given configuration.

  In addition, as another method for performing Y-direction detection / gradation expansion processing when the number of lines that can be stored in the line buffer 13 is limited, there is the following method.

  The false contour of a region having gradation change such as gradation is represented as a curve in the XY plane. That is, the false contour detected between adjacent lines is considered to have a high correlation. For this reason, it is also possible to perform gradation expansion processing from predicted detection data in the Y direction and detected data. The predicted detection data may be changed as needed based on the detected data.

  Further, a method is conceivable in which detection processing in the Y direction is executed based on the image signal of the previous frame, and the detection processing result is applied to the current frame image. This is a method utilizing the fact that the correlation of images between frames is usually very high. However, when the correlation between frames becomes low, such as when scenes are switched, it is necessary to provide means for checking the image quality and not executing the gradation expansion processing by linear interpolation.

  As described above, even when the line buffer 13 having a limited storage capacity is used due to problems such as cost, it is possible to perform detection / gradation expansion processing in a direction different from the arrangement direction of the image data stored in the line buffer 13. Therefore, more appropriate gradation expansion processing can be realized.

(Second Embodiment)
Next, an image processing apparatus according to a second embodiment of the present invention will be described.

  FIG. 11 is a block diagram showing the configuration of the second embodiment of the image processing apparatus of the present invention.

  The image processing apparatus according to the second embodiment includes a frame buffer 14 instead of the line buffer 13, and sends the image signals rearranged in the frame buffer 14 to the detection unit 11. This is different from the image processing apparatus of the embodiment.

  In such a configuration, the arrangement of the signal sequence sent from the frame buffer 14 to the detection unit 11 does not have to be the same as the signal sequence of the input image as in the image processing apparatus of the first embodiment.

  For example, when the input image is a raster image, the image data is sequentially sent from the upper left of the screen in the horizontal direction. In the present embodiment, the image data is arranged in the vertical direction with respect to the arrangement of the signal sequence of the raster image. In addition, the image data arranged continuously can be sent from the frame buffer 14 to the detection unit 11 in an arbitrary arrangement.

  Further, by detecting image data in a plurality of directions, for example, the horizontal direction (X direction) and the vertical direction (Y direction) by the detection unit 11, the detection position data is converted into two-dimensional coordinates (X, Y) as shown in FIG. ) And the gradation change amount can also be obtained by two-dimensional coordinates (FCx, FCy). For this reason, it is possible to execute gradation expansion processing with higher accuracy. For example, the extended correction unit 12 executes a gradation extended correction process on the X direction data and the Y direction data independently, and executes a process of adding the calculation results or a process of calculating an average value. Thus, the detection results in the two directions can be reflected in the gradation expansion process.

  According to the image processing apparatus of the present embodiment, since the frame buffer 14 is provided, it is possible to execute the detection / correction process not only in the arrangement direction of the image data of the input image but also in any direction. More appropriate gradation expansion processing can be executed.

  Further, in the image processing apparatus of the present embodiment, since the amount of change in the signal estimated as the noise / error component of one pixel and one gradation by the averaging correction unit 25 is reduced as in the first embodiment, Noise and error components can be suppressed.

(Third embodiment)
Next, a third embodiment of the present invention will be described.

  In the first and second embodiments, the example in which the image processing method of the present invention is applied to the image processing apparatus has been shown. However, the third embodiment is an image shown in the first and second embodiments. This is an example in which processing is applied to a display device.

  FIG. 12 is a block diagram illustrating a configuration example of the display device of the present invention.

  The display device according to the third embodiment stores a detection unit 11 that performs detection processing on a raster image composed of 8-bit image data sent from an information processing device such as a computer, and stores image data for one line. A line buffer 13, and an expansion correction unit 12 that expands the image data output from the line buffer 13 to 10 bits based on the detected position data X and the gradation change data FC sent from the detection unit 11, The image display unit 15 can display 10 bits.

  The display device of the third embodiment is the same as the configuration of the image processing device of the first embodiment shown in FIG. 6 except that the image display unit 15 is added. In the display device according to the third embodiment, the detection unit 11, the extended correction unit 12, and the line buffer 13 constitute an image processing unit.

  In this embodiment, the case where 8-bit image data is extended to 10 bits is described as an example. However, the processing method is different from the case where 6-bit image data is extended to 8 bits. It is not a thing.

  Since the display device sequentially processes image data for each line in the main scanning direction, the line buffer is preferably a buffer size that can store image data for one line in the X direction of the image display unit. The image display unit 15 may be any device such as an LCD, PDP, EL, CRT, etc., as long as it can display image data.

  As a result, even if the number of bits of the input image data is smaller than the number of bits that can be displayed on the image display unit 15, an appropriate gradation expansion process can be performed, the occurrence of false contours can be suppressed, and higher A high-quality display can be obtained.

  Also in the present embodiment, as in the first and second embodiments, the amount of change in the signal estimated as a noise / error component of one pixel and one gradation by the averaging correction unit 25 is reduced. Noise and error components can be suppressed.

(Fourth embodiment)
Next, a fourth embodiment of the present invention will be described with reference to the drawings.

  The fourth embodiment is an example of realizing the image processing method of the present invention using an information processing apparatus. That is, as shown in FIG. 13, the processing of the detection unit 11 and the extended correction unit 12 shown in the first embodiment is executed by a computer (CPU 31).

  FIG. 14, FIG. 15 and FIG. 16 are flowcharts showing the processing procedure of the image processing method of the present invention. 14 to 16 are examples in which the CPU 31 executes the processing of the image processing apparatus shown in the first embodiment.

  The image processing method of the present invention performs detection processing on an input 6-bit raster image, and performs extension processing to 8 bits based on the detection result. The processing from step S2 to step S12 shown in FIG. 14 corresponds to the processing of the detection unit 11 (first image processing) shown in the first embodiment, and the processing from step S13 to step S28 shown in FIG. 15 and FIG. The processing corresponds to the processing of the extended correction unit 12 (second image processing) shown in the first embodiment.

  The CPU 31 executes these processes in accordance with a program stored in a ROM (not shown) or a recording medium provided in the computer, thereby realizing the functions of the detection unit 11 and the extended correction unit 12 described above.

  First, the first image processing will be described with reference to FIG.

  As shown in FIG. 14, when the image data In (6 bits) of the raster image 1 is input to the computer, the CPU 31 displays information indicating which pixel the input image signal is (that is, y of the pixel). Value) is extracted (step S1). Here, In () indicates a gradation value.

  The CPU 31 initializes the input signal position x0 = 0 and obtains a predetermined data length Xmax in the X direction in order to perform detection / correction processing on the image data of the line based on the Y coordinate of the pixel (step S2). ).

  In addition, the CPU 31 sets the start point position Xs = 0, the start point previous position Xs0 = 0, the start point gradation Ts = In (0, y), the start point change FCs = 10, and the threshold value TH = 2 at the start of the detection process ( Step S3).

  When initial conditions are set, the detection process is as follows.

  First, the CPU 31 increments the input signal position x0 by 1 (step S4).

  Subsequently, if the value of x0 is equal to Xmax, the gradation change detection process is terminated, and the process proceeds to step S7. Otherwise, the process proceeds to the gradation change detection process (step S5).

(Gradation change detection processing)
Next, the CPU 31 determines that the gradation data In (x0, y) at the position x0 is equal to the starting point gradation Ts (the same gradation is continuous), or Ts−TH <In (x0, y) <Ts + TH. If In (x0 + 1, y) = Ts (change in one pixel and one gradation), the process returns to step S4 to continue detecting gradation change. Otherwise, it is regarded as a gradation change point, and the process proceeds to step S7 (step S6).

  Subsequently, the CPU 31 holds the values of the end point position Xe = x0 and the end point gradation Te = In (x0, y) (step S7).

(Detection point change amount setting process)
Next, when Ts−TH <In (x0, y) <Ts + TH and In (x0 + 1, y) = In (x0, y) (determination as to whether the region is a linear interpolation application region) The process proceeds to step S9, and if not, the process proceeds to step S10 (step S8).

  In step S9, In (x0, y) and Ts are compared, and an increase or decrease in gradation change in the linear interpolation application region is determined. If the gradation change increases, the process proceeds to step S11. If the gradation change decreases, the process proceeds to step S12.

  In step S10, the end point change Te is set to 10 (not the linear interpolation application region).

  In step S11, the end point change Te is set to 00 (the gradation change increases in the linear interpolation application region).

  In step S12, the end point change Te is set to 01 (the gradation change is reduced in the linear interpolation application region).

  The CPU 31 shifts to the gradation expansion process that is the second image process while holding the parameters obtained in steps S10 to S12.

  Next, the second image processing will be described with reference to FIGS. 15 and 16.

  As shown in FIG. 15, the CPU 31 first sets the expansion correction signal position x to Xs (step S13).

(Gradation expansion content determination process)
Next, the CPU 31 determines a gradation expansion process to be applied based on the values of the start point gradation change FCs and the end point gradation change FCe (step S14 to step S17). The procedure for determining the contents of gradation expansion processing is as follows (1) to (5).

  (1) If FCs = 00 and FCe = 01, the process of step S18 is executed (step S14).

  (2) If the condition (1) is not satisfied, FCs = 01, and FCe = 00, the process of step S19 is executed (step S15).

  (3) If the condition (2) is not satisfied and FCe = 00, the process of step S20 is executed (step S16).

  (4) If the condition (3) is not satisfied and FCs = 01, the process of step S21 is executed (step S17).

  (5) If the condition (4) is not satisfied, the process of step S22 is executed (step S17).

(Gradation expansion processing)
The CPU 31 uses the start point position Xs, the start point gradation Ts, the end point position Xe, the end point gradation Te, the extended correction signal position x, and the input image signal, and processes (1) to (5) shown below. Among them, any one of the gradation expansion processes is executed according to the selection result from step S14 to step S17.

(1) Step S18:
Out ′ (x) = 4 * [In (Xs) − (In (Xe) −In (Xs)) / 2 * {1-abs (x * 2−Xs−Xe) / (Xe−Xs)}]
(2) Step S19:
Out '(x) = 4 * [In (Xe)-(In (Xe) -In (Xs)) / 2 * {1-abs (x * 2-Xs-Xe) / (Xe-Xs)}]
(3) Step S20:
Out ′ (x) = 4 * [In (Xs) + (In (Xe) −In (Xs)) * (x−Xs) / (Xe−Xs)]
(4) Step S21:
Out ′ (x) = 4 * [In (Xs0) + (In (Xs) −In (Xs0)) * (x−Xs) / (Xe−Xs)]
(5) Step S22 (does not perform linear interpolation processing):
Out ′ (x) = 4 * In (x)
(Averaging correction process)
Next, the CPU 31 compares In (x, y) with Ts and executes one of the following processes (step S23).

When In (x) ≠ Ts: Out (x) = (In (x) + Out ′ (x)) / 2
・ Others: Out (x) = Out '(x)
Subsequently, the CPU 31 increments the value of x by 1 (step S24).

  If x <Xe, the same parameter Xs. Ts. Xe. In order to repeat the gradation expansion process using Te, the process returns to step S14. If x ≧ Xe, the gradation expansion process is terminated (step S25).

  Next, the CPU 31 compares the values of x0 and Xmax (step S26). If x0 = Xmax, the CPU 31 calculates the scale for all input signals In (x, y) for one line from x = 0 to Xmax. Since the key expansion process is performed, the process proceeds to step S29. Otherwise, the process proceeds to step S27 in order to continue processing for the remaining input signals.

  In step S27, the CPU 31 substitutes Xs for the position Xs0 before the start point.

  Subsequently, Xe is substituted for the start point position Xs, Te is substituted for the start point gradation Ts, FCe is substituted for the start point change FCs (step S28), and the process returns to step S4 to restart the detection process.

  The CPU 31 outputs the output image data Out (x, y) (8 bits) obtained by the above processing (step S29).

  As described above, the processing of the detection unit 11 (first image processing) and the processing of the expansion correction unit 12 (second image processing) shown in the first embodiment are executed by a computer, so that The image processing similar to that of the image processing apparatus according to the first embodiment can be executed without using hardware.

  Note that the flowcharts shown in FIGS. 14 to 16 show the processing of the image processing apparatus of the first embodiment, but the processing of the image processing apparatus of the second embodiment is similar to the above. It is possible to execute using

  In the fourth embodiment, the case where the processing for reducing the data capacity of the raster image and the processing for decompressing and restoring the image data are executed by the computer according to the program has been described as an example. Only one of the processes may be executed by a computer.

  In the fourth embodiment, an example in which the functions of the image processing apparatus according to the first embodiment are realized using a computer has been described. However, the processing of the image detection apparatus and the gradation expansion apparatus described above is also performed by a computer. Needless to say, this can be achieved with

  In the first to fourth embodiments described above, the number of bits of image data increased by gradation expansion may be described as being constant. However, the number of bits increased after gradation expansion may be an arbitrary number. Applicable.

  Moreover, the said 1st Embodiment-4th Embodiment show a suitable example of this invention, and this invention is the structure shown in 1st Embodiment-4th Embodiment. It is not limited. For example, the bit increase amount of the image data for each color by the gradation expansion process does not need to be the same. That is, when the image data is composed of three systems of RGB, R data is 5 bits, G data is 6 bits, and B data is 5 bits, R data and B data are expanded by 3 bits, and G data is 2 bits. By expanding the bits, it is possible to make each RGB image data 8 bits.

  Further, the configuration may be such that only the number of bits of a part of the RGB image data is increased. The raster image does not necessarily need to be a color image composed of image data of a plurality of colors, and may be a monochrome image.

  Further, in the present embodiment, an example in which a change in one gradation per pixel is estimated as a noise / error component has been described. However, as shown in the principle of the invention, n pixels 1 in accordance with the definition of an image and a display device. The detection process may be executed using a change in gradation as a noise / error component. As described above, the present invention can be variously modified.

It is a schematic diagram which shows an example of the conventional detection process and linear interpolation process in a gradation expansion process. It is a schematic diagram which shows the other example of the conventional detection process and linear interpolation process in the gradation expansion process at the time of adding a noise component to the image signal shown in FIG. It is a schematic diagram which shows an example of the detection process and linear interpolation process of this invention in the gradation expansion process at the time of adding a noise component to the image signal shown in FIG. It is a schematic diagram which shows the other example of the detection process and linear interpolation process of this invention in the gradation expansion process at the time of adding a noise component to the image signal shown in FIG. It is a schematic diagram which shows the other example of the linear interpolation process in a gradation expansion process. 1 is a block diagram illustrating a configuration of a first embodiment of an image processing apparatus of the present invention. It is a block diagram which shows one structural example of the detection part with which the image processing apparatus shown in FIG. 6 is provided. It is a schematic diagram which shows the process of the detection part with which the image processing apparatus shown in FIG. 6 is provided. It is a block diagram which shows one structural example of the extended correction | amendment part with which the image processing apparatus shown in FIG. 6 is provided. It is a schematic diagram which shows the process of the extended correction | amendment part with which the image processing apparatus shown in FIG. 6 is provided. It is a block diagram which shows the structure of 2nd Embodiment of the image processing apparatus of this invention. It is a block diagram which shows the example of 1 structure of the display apparatus of this invention. It is a block diagram which shows the example of 1 structure of the information processing apparatus which implement | achieves the image processing method of this invention. It is a flowchart which shows the procedure of the image processing method of this invention. It is a flowchart which shows the procedure of the image processing method of this invention. It is a flowchart which shows the procedure of the image processing method of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 11 Detection part 12 Extended correction part 13 Line buffer 14 Frame buffer 15 Image display part 21 Judgment output part 22 Start point parameter holding part 23 Counter 24 Correction process part 25 Average correction part 26 Parameter extraction part 27 Parameter buffer 31 CPU

Claims (12)

By sequentially scanning the pixel sequence of the input digital image signal, the linear interpolation application region, which is a region in which gradation change processing by linear interpolation is performed on the pixel sequence of the digital image signal to smooth the gradation change, is performed. A detection unit for detecting;
An expansion correction unit that performs gradation expansion processing on the linear interpolation application region detected by the detection unit;
An image processing apparatus comprising:
The detector is
When a gradation change within a predetermined range is detected when sequentially scanning the gradation value of the pixel row of the input digital image signal, the gradation of the pixel at the position next to the position where the gradation change is detected If the value is the same as the gradation value of the pixel at the position before the position where the gradation change is detected, the gradation value of the pixel where the gradation change is detected is set to the level of the pixel at the position before and after the pixel. An image processing apparatus regarded as a key value. By sequentially scanning the pixel sequence of the input digital image signal, the linear interpolation application region, which is a region in which gradation change processing by linear interpolation is performed on the pixel sequence of the digital image signal to smooth the gradation change, is performed. A detection unit for detecting;
An expansion correction unit that performs gradation expansion processing on the linear interpolation application region detected by the detection unit;
An image processing apparatus comprising:
The detector is
When the gradation value of the pixel row of the input digital image signal is sequentially scanned, if a gradation change within a predetermined range is detected, the same gradation is detected at a plurality of pixels from the position where the gradation change is detected. If the gradation value of the pixel at the next position is the same as the gradation value of the pixel at the position before the position where the gradation change is detected, the value of the pixel where the gradation change is detected An image processing apparatus that regards gradation values as gradation values of pixels at positions before and after the pixel. The extended correction unit is
A correction processing unit that performs correction processing on the input digital image signal based on detection position data and a gradation change amount in the detection unit;
The digital image signal and the output image signal from the correction processing unit are input, an average value of the image signal subjected to the correction processing from the correction processing unit and the digital image signal is calculated, and the digital image An averaging correction unit that outputs the average value when the gradation value of the signal is not the same as the start point gradation of the linear interpolation application region; otherwise, an averaging correction unit that outputs the output image signal from the correction processing unit as it is; ,
The image processing apparatus according to claim 1, further comprising:   4. The image processing apparatus according to claim 1, further comprising a line buffer for storing at least an image signal for one line of the digital image signal.   4. The image processing apparatus according to claim 1, further comprising a frame buffer for storing at least an image signal for one screen of the digital image signal. The gradation change within the predetermined range is
The image processing apparatus according to claim 1, wherein the image processing apparatus is a gradation change of a minimum gradation difference of the digital image signal. The detector is
7. The region according to claim 1, wherein a region satisfying a condition that adjacent regions having the same tone value are adjacent and a tone difference between the regions is within a predetermined value is detected as the linear interpolation application region. The image processing apparatus described. By sequentially scanning the pixel sequence of the input digital image signal, the linear interpolation application region, which is a region in which gradation change processing by linear interpolation is performed on the pixel sequence of the digital image signal to smooth the gradation change, is performed. When a gradation change within a predetermined range is detected when detecting, the gradation value at the position next to the position where the gradation change is detected is the pixel at the position before the position where the gradation change is detected. A detection unit that regards the gradation value of the pixel in which the gradation change is detected as a gradation value of a pixel at a position before and after the pixel, and linear interpolation detected by the detection unit An image processing unit including an expansion correction unit that performs gradation expansion processing on the application area;
A display unit for displaying an image based on an output signal of the image processing unit;
A display device. By sequentially scanning the pixel sequence of the input digital image signal, the linear interpolation application region, which is a region in which gradation change processing by linear interpolation is performed on the pixel sequence of the digital image signal to smooth the gradation change, is performed. When detecting a change in gradation within a predetermined range at the time of detection, the same gradation value continues in a plurality of pixels from the position where the gradation change is detected, and the gradation value of the pixel at the next position is detected. Is the same as the gradation value of the pixel at the position before the position where the gradation change is detected, the gradation value of the pixel where the gradation change is detected is the gradation value of the pixel at the position before and after the pixel. A detection unit that is regarded as a value, and an image processing unit that includes an expansion correction unit that performs gradation expansion processing on the linear interpolation application area detected by the detection unit;
A display unit for displaying an image based on an output signal of the image processing unit;
A display device. By sequentially scanning the pixel sequence of the input digital image signal, the linear interpolation application region, which is a region in which gradation change processing by linear interpolation is performed on the pixel sequence of the digital image signal to smooth the gradation change, is performed. An image processing method comprising: a step of detecting; and a step of performing gradation expansion processing on the detected linear interpolation application region,
The step of detecting the linear interpolation application region includes:
When a gradation change within a predetermined range is detected when sequentially scanning the gradation value of the pixel row of the input digital image signal, the gradation of the pixel at the position next to the position where the gradation change is detected If the value is the same as the gradation value of the pixel at the position before the position where the gradation change is detected, the gradation value of the pixel where the gradation change is detected is set to the level of the pixel at the position before and after the pixel. An image processing method that is regarded as a key value. By sequentially scanning the pixel sequence of the input digital image signal, the linear interpolation application region, which is a region in which gradation change processing by linear interpolation is performed on the pixel sequence of the digital image signal to smooth the gradation change, is performed. An image processing method comprising: a step of detecting; and a step of performing gradation expansion processing on the detected linear interpolation application region,
The step of detecting the linear interpolation application region includes:
When the gradation value of the pixel row of the input digital image signal is sequentially scanned, if a gradation change within a predetermined range is detected, the same gradation is detected at a plurality of pixels from the position where the gradation change is detected. If the gradation value of the pixel at the next position is the same as the gradation value of the pixel at the position before the position where the gradation change is detected, the value of the pixel where the gradation change is detected An image processing method that regards a gradation value as a gradation value of a pixel at a position before and after the pixel.   The program for making a computer perform the image processing method of Claim 10 or 11.

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