JP4687673B2 - Monotone processing of color image - Google Patents

Description

  The present invention relates to a technique for performing monotone conversion of color image data.

  An image taken by an image generation device such as a digital still camera, a digital video camera, or a scanner is output (displayed or printed) by various image output devices such as a monitor or a printer. As an image output device, an LCD display, a color inkjet printer, or the like that can output a color image is widely used, and the user can easily use the color image.

  While color images are widely used, monotone images are also widely preferred. A monotone image can express a unique atmosphere by reminiscent of an old photograph. Therefore, a method of converting color image data into monotone image data and using it is used (for example, see Patent Document 1).

JP 2002-337323 A

  One important factor that determines the image quality is the appearance of the subject. If the subject appears to stand out, the user can recognize the image as a high-quality image. In a color image, if the subject's hue is different from the surrounding hue, the subject appears to stand out. However, in a monotone image, even if the hue is different, a region with close brightness is expressed with close gradation. As a result, even when the monotone processing of the color image data is uniformly performed, the contrast between the subject and the surrounding area becomes weak, and there is a possibility that a high-quality monotone image cannot be obtained.

  The present invention has been made to solve the above-described conventional problems, and an object of the present invention is to provide a technique for executing a monotone process suitable for color image data.

In order to achieve at least a part of the above object, an image processing apparatus of the present invention is based on color image data generated by an image generation apparatus and a shooting mode of the image generation apparatus at the time of generation of the color image data. An image processing apparatus that performs monotone conversion of the color image data, wherein a pixel value that represents the color of each pixel of the color image data is a pixel that represents the brightness of each pixel of the monotone image data based on the shooting mode. A brightness conversion formula adjusting section that adjusts a brightness conversion formula to be converted into a value; and a brightness conversion section that generates monotone image data of the color image data in accordance with the adjusted brightness conversion formula.

Since this image processing apparatus performs monotone processing based on the shooting mode, it can execute monotone processing suitable for color image data.

In the image processing apparatus, the brightness conversion type adjustment unit may be configured such that when the shooting mode is a shooting mode suitable for a human image, compared to a shooting mode under a standard shooting condition of the image generation device. It is preferable to adjust the brightness conversion formula so that the brightness of the pixel of the monotone image data with respect to the pixel having the skin color of the color image data becomes bright.

  According to this configuration, when the operation mode is suitable for a human image, the monotone processing is performed so that the brightness of the pixels having the flesh color becomes brighter, so that high-quality monotone image data that makes the person stand out is generated. can do.

In each of the image processing devices described above, the brightness conversion type adjustment unit may be configured such that when the shooting mode is a shooting mode suitable for a landscape image, compared to a shooting mode under the standard shooting conditions of the image generation device, It is preferable to adjust the lightness conversion formula so that the brightness of the pixels of the monotone image data with respect to the pixels having the sky blue color of the color image data becomes dark.

  According to this configuration, when the operation mode is suitable for a landscape image, the monotoning process is performed so that the brightness of the green pixel is darkened. Data can be generated.

  The present invention can be realized in various forms, for example, an image processing method and an image processing apparatus, a computer program for realizing the function of the method or apparatus, and a recording in which the computer program is recorded. It can be realized in the form of a medium or the like.

Next, embodiments of the present invention will be described in the following order based on examples.
A. Device configuration:
B. First embodiment:
C. Second embodiment:
D. Third embodiment:
E. Fourth embodiment:
F. Fifth embodiment:
G. Variations:

A. Device configuration:
FIG. 1 is an explanatory diagram showing the configuration of an image output system as an embodiment of the present invention. This system includes a digital camera 100, a computer 200, and a printer 300. The digital camera 100 functions as an image generation device, the computer 200 functions as an image processing device, and the printer 300 functions as an image output unit. Color image data generated by the digital camera 100 is transferred to the computer 200. The computer 200 executes monotone processing suitable for the received color image data to generate monotone image data. The computer 200 further generates print data according to the monotone image data and sends it to the printer 300. The printer 300 performs printing according to the received print data.

B. First embodiment:
B1. Configuration of image processing device:
FIG. 2 is a block diagram illustrating a configuration of the computer 200. The computer 200 includes a data processing unit 220 and a print data generation unit 240. The data processing unit includes a lightness conversion unit 222, a lightness conversion expression adjustment unit 224, and an image data analysis unit 226.

  The image data analysis unit 226 analyzes the color image data to be processed and generates color distribution information related to the color deviation. The lightness conversion formula adjustment unit 224 adjusts the lightness conversion formula based on the color distribution information. The lightness conversion unit 222 executes lightness conversion processing on the color image data to be processed according to the lightness conversion formula, and generates monotone image data. Details of the processing of these functional units will be described later.

  The print data generation unit 240 generates print data according to the monotone image data generated by the data processing unit 220. In this embodiment, the print data generation unit 240 executes conversion processing from pixel values of each pixel of the monotone image data to multi-gradation data corresponding to a plurality of ink amounts that can be used by the printer 300. Print data is generated by performing halftone processing on the multi-tone data. The conversion process into multi-gradation data corresponding to the amount of ink is a kind of color space conversion process, and is usually executed based on a lookup table that represents the correspondence between input values and output values.

  The print data generated by the print data generation unit 240 is sent to the printer 300 and printed. The printer 300 includes various components such as a main scanning drive mechanism, a sub-scanning drive mechanism, a print head, a print head drive circuit, and a control circuit, but the description thereof is omitted here.

  Note that the monotone expression is not limited to an expression that reproduces gradation using a pure achromatic color (so-called neutral expression), and there are expressions with various colors. For example, there are expressions that give various color feelings such as yellow and blue, such as a warm expression that expresses a gradation using yellowish gray and a cool expression that expresses a gradation using blueish gray.

  Such a color sensation can be expressed by using the look-up table prepared by the print data generation unit 240 corresponding to various monotone expressions. For example, the look-up table for warm expression is set to perform conversion from pixel values representing the brightness of each pixel of monotone image data to multi-gradation data that expresses gradation using yellowish gray. Is done. It should be noted that multi-tone data representing such colored gradation can also be referred to as monotone image data.

  Further, the data processing unit 220 may generate monotone image data expressing various color sensations. Such monotone image data can be generated by calculating a pixel value representing a gradation having a specific color based on the pixel value representing the brightness generated by the lightness conversion unit 222. The data processing unit 220 can generate monotone image data expressing various color sensations by including a color sensation adjusting unit (not shown) that performs such color sensation adjustment processing. In the following description, multi-tone data with only lightness created by the data processing unit 220 executing lightness conversion processing is referred to as monotone image data.

  Note that the functions of some or all of the components in the computer 200 as described above are realized by a computer program, for example. These computer programs can be provided in a form recorded on a computer-readable recording medium such as a flexible disk or a CD-ROM.

B2. Monotone processing:
FIGS. 3A and 3B are explanatory diagrams for explaining characteristic color information generated by the image data analysis unit 226 (FIG. 2) analyzing color image data in the first embodiment. In the present embodiment, the image data analysis unit 226 calculates the ratio of sky blue pixels as characteristic color information. FIG. 3A shows an example of an image showing an image of the sky over the city as an object, and FIG. 3B shows an example of a hue histogram of an image of the sky as an object. Has been.

  The hue H of each pixel can be calculated based on the pixel value of each pixel. In this embodiment, in order to calculate the hue H, a conversion formula from the RGB color space to the HSI color space is used. The HSI color space is a color space having hue H, saturation S, and lightness I as parameters. Also, the hue H can be calculated using other appropriate color spaces such as the HSV color space and the HSL color space.

  The relationship between the pixel values R, G, and B expressed in the RGB color space and the hue H expressed in the HSI color space is expressed by the following equation.

  Here, Imax = max {R, G, B} and Imin = min {R, G, B}. When Imax = Imin, the hue H is indefinite (achromatic). When hue H <0, 2π is added to the calculated hue H value. As a result, the value range of the hue H is 0 to 2π, but in this embodiment, the hue H is expressed by setting the value range to 0 degree to 360 degrees.

  In this embodiment, a hue range is set for three characteristic colors of skin color, green color, and sky blue color. Specifically, the range where the hue H is 0 degree to 30 degrees is the skin color range SR, the range where the hue is 100 degrees to 130 degrees is the green range GR, and the range where the hue is 230 degrees to 260 degrees is the sky blue range BR. (FIG. 3B). Further, the image data analysis unit 226 calculates a sky_rate ratio of sky blue pixels, that is, pixels having a hue in the sky blue range BR. Note that the hue range is not necessarily the above-described range, and a different range may be set.

  FIGS. 4A and 4B are explanatory diagrams for explaining adjustment of the brightness conversion formula in the first embodiment. FIG. 4A is an explanatory diagram illustrating the determination condition of the target color by the lightness conversion equation adjusting unit 224 (FIG. 2). Here, the target color is a color representing the characteristics of the subject, and means a color that is easy for the observer of the image to focus on. In the present embodiment, the lightness conversion formula adjusting unit 224 determines the target color based on the sky blue rate sky_rate. When the sky blue rate sky_rate is larger than the sky blue threshold sky_th, it is determined that the sky is a landscape image with the sky as a subject, that is, the target color is sky blue. When the sky blue rate sky_rate is equal to or less than the sky blue threshold sky_th, it is determined that the image is a standard image in which a specific target color cannot be determined, that is, the target color is a standard.

  The sky blue threshold sky_th described above is preferably set so as to increase the accuracy of the determination. Further, a specific value may be set as an initial value so that the user can change the value.

  FIG. 4B is an explanatory diagram illustrating the brightness conversion formula adjusted by the brightness conversion formula adjustment unit 224. In the upper part of FIG. 4B, pixel values R, G, and B representing the color of each pixel of the color image data, and a pixel value Y (also referred to as a luminance value) representing the brightness of each pixel of the monotone image data. An example of a lightness conversion equation showing the relationship is shown.

  In the brightness conversion formula of this embodiment, the luminance value Y is represented by a linear combination of three pixel values R, G, and B. The coefficient of each pixel value R, G, B is represented by the sum of standard values kr_std, kg_std, kb_std and adjustment values Δkr, Δkg, Δkb, respectively.

  In the lower part of FIG. 4B, the relationship between the adjustment values Δkr, Δkg, Δkb and the target color is shown. If the target color is a standard color, any adjustment values Δkr, Δkg, Δkb are set to zero. As a result, the luminance value Y and the pixel values R, G, and B are associated with each other by a standard relational expression based on the standard values kr_std, kg_std, and kb_std.

  When the target color is sky blue, the adjustment value Δkr of the red component R is set to a positive value, and the adjustment values Δkg and Δkb of the green component G and the blue component B are set to negative values. As a result, the luminance value Y of a pixel having a hue close to green or blue is set to a smaller value than when the target color is standard. On the other hand, the luminance value Y of a pixel having a hue close to red is set to a larger value than when the target color is standard.

  As the standard values kr_std, kg_std, and kb_std, standard values, for example, values based on conversion formulas from the parameter values R, G, and B in the RGB color space to the luminance value Y in the YCbCr color space are used. Can do. The magnitudes of the adjustment values Δkr, Δkg, and Δkb are preferably set so that the obtained monotone image does not become unnatural, and can be determined based on the sensitivity evaluation of the image quality adjustment result.

  Hereinafter, such a brightness conversion formula set according to the target color is referred to as a brightness conversion formula corresponding to the color.

  FIG. 5 is an explanatory diagram illustrating an example of a monotone image with respect to the image illustrated in FIG. In the image shown in FIG. 3A, it is assumed that the ratio sky_rate of sky blue pixels is larger than the sky blue threshold sky_th, and the target color is sky blue. Accordingly, the lightness conversion unit 222 (FIG. 2) performs lightness conversion processing using the lightness conversion formula corresponding to the sky blue. In this embodiment, the lightness conversion unit 222 applies the lightness conversion formula set as shown in FIG. 4B to all the pixels of the color image data to be processed. As a result, in the monotone image shown in FIG. 5, the brightness of the sky is kept low, and the contrast with the surrounding background (town in this example) becomes strong. In this way, by performing the lightness conversion process using the lightness conversion formula corresponding to the sky blue, it is possible to obtain high-quality monotone image data in which the sky is attractive.

  As described above, in this embodiment, the brightness conversion formula can be automatically adjusted according to the sky blue rate sky_rate. As a result, an appropriate monotone process can be performed according to the color image data.

  Note that the sky color ratio sky_rate in the present embodiment corresponds to the characteristic color information in the present invention.

C. Second embodiment:
The difference from the first embodiment is that the brightness conversion formula is adjusted based on the pixel ratio of each of the three characteristic colors (skin color, green color, sky blue). The configuration of the image processing apparatus is the same as in FIG.

  FIGS. 6A and 6B are explanatory diagrams for explaining adjustment of the lightness conversion formula in the second embodiment. FIG. 6A is an explanatory diagram illustrating determination conditions for a target color by the lightness conversion formula adjustment unit 224 (FIG. 2). The difference from the example shown in FIG. 4A is that the target color is determined based on the ratios skin_rate, green_rate, and sky_rate (FIG. 3B) of each of the three characteristic colors (skin color, green color, sky blue). It is a point. The ratio of these pixels is calculated by the image data analysis unit 226.

  In the present embodiment, among the characteristic colors, the one with the largest pixel ratio is adopted as the target color candidate. Furthermore, when the ratio of pixels is larger than the threshold value corresponding to each characteristic color, it is adopted as the target color. For example, when the skin color ratio skin_rate is the largest of the three ratios skin_rate, green_rate, and sky_rate, the skin color is adopted as the target color candidate. Further, when the skin color ratio skin_rate is larger than the skin color threshold skin_th, it is determined that the image is a person image having a person as a subject, that is, the target color is a skin color. On the other hand, when the skin color ratio skin_rate is equal to or less than the skin color threshold skin_th, it is determined that the target color is the standard.

  Similarly, when the green ratio green_rate is the largest, a determination regarding green is performed. When the green ratio green_rate is larger than the green threshold green_th, it is determined that the image is a landscape image with forests and mountains as subjects, that is, the target color is green. Similarly, when the sky blue rate sky_rate is the highest, determination regarding sky blue is performed.

  FIG. 6B is an explanatory diagram illustrating the brightness conversion formula adjusted by the brightness conversion formula adjustment unit 224 in the present embodiment. A difference from the example illustrated in FIG. 4B is that a case where the target color is a skin color and a case where the target color is green are added.

  When the target color is a skin color, the adjustment values Δkr and Δkg of the red component R and the green component G are set to positive values, and the adjustment value Δkb of the blue component B is set to a negative value. Therefore, the luminance value Y of a pixel having a hue close to red or green is set to a larger value than when the target color is standard. On the other hand, the luminance value Y of a pixel having a hue close to blue is set to a smaller value than when the target color is standard. By adjusting the brightness conversion formula in this way, the brightness after conversion of the pixels having the flesh color in the image is set higher. As a result, it is possible to generate high-quality monotone image data in which a person stands out.

  When the target color is green, the adjustment value Δkg of the green component G is set to a negative value, and the adjustment values Δkr and Δkb of the red component R and the blue component B are set to positive values. Accordingly, the luminance value Y of a pixel having a hue close to green is set to a smaller value than when the target color is standard. On the other hand, the luminance value Y of a pixel having a hue close to red or blue is set to a larger value than when the target color is standard. By adjusting the brightness conversion formula in this way, the brightness after conversion of the green pixels in the image can be kept low. As a result, it is possible to generate high-quality monotone image data in which plants and mountains stand out.

  Thus, in the present embodiment, the brightness conversion formula can be automatically adjusted according to the respective pixel ratios of skin color, green color, and sky blue. As a result, it is possible to perform monotone processing suitable for various subjects represented by color image data.

  When determining the target color, instead of simply comparing the pixel ratio, a weight set in advance according to the characteristic color may be added to the pixel ratio for comparison. For example, the skin color ratio skin_rate in the person image tends to be smaller than the green ratio green_rate and the sky blue ratio sky_rate in the landscape image. Even in such a case, if the weight for the skin color ratio skin_rate is increased and compared, the accuracy of determining the target color as the skin color for the person image can be increased.

  Alternatively, priority order may be set for characteristic colors, and the target color may be determined in the order of priority order. For example, the priority order is the order of skin color, green, and sky blue. In this case, first, a determination is made to compare the pixel ratio and the threshold value for the skin color. If it is not possible to determine that the target color is a skin color, the green color is determined. Hereinafter, the determination is performed in the order according to the priority order. Thus, by determining the target color according to the priority order, it is possible to improve the accuracy of the target color determination for various color image data.

D. Third embodiment:
In the first and second embodiments described above, the same brightness conversion formula is applied to all pixels, but different brightness conversion formulas may be applied depending on the pixels. FIG. 7 is an explanatory diagram showing a state in which a plurality of brightness conversion formulas are applied to one color image data. FIG. 7 shows an image showing the sky and a person spreading over the city.

  In this embodiment, in order to perform such monotone processing suitable for a plurality of subjects, a brightness conversion formula is set independently for each pixel of a plurality of characteristic colors. Specifically, the lightness conversion type adjustment unit 224 (FIG. 2) is based on the ratio of each pixel and the threshold value for a pixel group having each of three characteristic colors (skin color, green color, sky blue color). Prepare brightness conversion formulas independently.

  The brightness conversion type adjustment unit 224 performs determination based on the pixel ratio and the threshold value for each of the three characteristic colors (skin color, green color, sky blue color). This determination is the same as the condition shown in FIG. For a feature color having a ratio larger than the threshold value, a brightness conversion formula (FIG. 6B) corresponding to the feature color is prepared. For the characteristic color whose ratio is equal to or less than the threshold value, a standard brightness conversion formula is prepared for the target color. For pixels that do not have any characteristic color, a standard brightness conversion formula is prepared for the target color. The lightness conversion unit 222 applies a lightness conversion formula corresponding to the color of each pixel of the color image data.

  In the example shown in FIG. 7, a brightness conversion formula corresponding to the skin color is applied to the skin color pixels. A lightness conversion formula corresponding to the sky blue is applied to the sky blue pixels. For the other pixels, the brightness conversion formula when the target color is standard is applied. As a result, since the brightness of the skin color is set high and the brightness of the sky is set low, it is possible to generate powerful monotone image data in which the contrast between the person and the sky is enhanced.

  As described above, in this embodiment, since the brightness conversion formula is properly used according to the color of the pixel of the color image data, even when processing color image data including various subjects, the monotonization suitable for a plurality of subjects is possible. Processing can be performed.

E. Fourth embodiment:
In the above-described embodiments, the magnitudes of the adjustment values Δkr, Δkg, Δkb of the lightness conversion formula may be variable values according to the pixel ratio of each characteristic color. For example, in the examples shown in FIGS. 6A and 6B, the absolute values of the adjustment values Δkr, Δkg, and Δkb may be adjusted so as to increase as the maximum pixel ratio increases. For example, among the three pixel ratios, when the sky blue ratio sky_rate is the maximum, the larger the sky blue ratio sky_rate, the larger the Δkr and the smaller the Δkg and Δkb (the absolute value is larger). . In this way, when the ratio of the pixels having the characteristic color is relatively large, the contrast between the subject having the characteristic color and the surrounding area can be increased more effectively. At this time, regarding plus and minus of the adjustment values Δkr, Δkg, and Δkb, it is preferable to follow the setting of the brightness conversion equation corresponding to the characteristic color having the maximum pixel ratio.

  Instead of determining the target color, the coefficients of the three pixel values R, G, and B of the brightness conversion equation may be defined by a function based on the pixel ratio of each characteristic color. Such a brightness conversion formula is represented by the following arithmetic formula, for example.

  In the formula, fr, fb, and fg are functions of the pixel ratios skin_rate, green_rate, and sky_rate of the three characteristic colors, respectively, and are the coefficients of the three pixel values R, G, and B, respectively.

  Thus, if the brightness conversion formula is expressed by a function of the pixel ratio, the brightness conversion formula can be finely adjusted in accordance with various color image data. As a result, it is possible to perform appropriate monotone processing corresponding to various color image data.

F. Fifth embodiment:
FIG. 8 is an explanatory diagram illustrating a configuration of an image data file IDF that can be used by the image processing apparatus according to the present exemplary embodiment. The image data file IDF includes shooting mode information INF and color image data IMG. The shooting mode information INF is information relating to setting of an operation mode (hereinafter referred to as a shooting mode) when the digital camera 100 is shooting.

  Some digital cameras can switch a shooting mode according to a shooting scene such as a person or a landscape. As the shooting mode, it is possible to select one of a plurality of modes prepared in advance such as a standard mode, a portrait mode (portrait mode), a landscape mode, and the like according to the type of subject. The standard mode is a default shooting condition (standard shooting condition) in the digital camera 100. The standard shooting conditions are often used as settings at the time of purchase of the digital camera 100. In addition, some digital cameras store information related to a shooting mode at the time of shooting (shooting mode information INF) as image data related information related to image data, together with image data, in an image data file. In this embodiment, such an image data file can be used. An example of such a file format is the Exif file format.

  FIG. 9 is a block diagram showing a configuration of a computer 200a in the fifth embodiment. The difference from the computer 200 shown in FIG. 2 is that the data processing unit 220 a includes a shooting mode information analysis unit 228 instead of the image data analysis unit 226. The shooting mode information analysis unit 228 analyzes the shooting mode information INF included in the image data file IDF and acquires the shooting mode. The brightness conversion formula adjustment unit 224a adjusts the brightness conversion formula according to the acquired shooting mode. In this embodiment, the shooting mode information analysis unit 228 corresponds to the operation mode determination unit in the present invention.

  FIG. 10 is an explanatory diagram showing a lightness conversion equation adjusted by the lightness conversion equation adjusting unit 224a. The difference from the examples shown in FIGS. 4B and 6B is that the adjustment values Δkr, Δkg, and Δkb are set according to the shooting mode. In this embodiment, in the case of the standard mode, any adjustment values Δkr, Δkg, Δkb are set to zero.

  In the portrait mode, the adjustment values Δkr and Δkg of the red component R and the green component G are set to positive values, and the adjustment value of the blue component B is set as in the case where the target color is the skin color in FIG. Δkb is set to a negative value. As a result, the brightness after conversion of skin-colored pixels in the image is set higher than in the standard mode.

  In the landscape mode, the adjustment value Δkr of the red component R is set to a positive value as in the case where the target color is sky blue in FIG. 6B, and the adjustment values Δkg, Δkb is set to a negative value. As a result, the brightness after conversion of sky blue pixels in the image is set lower than in the standard mode.

  The lightness conversion unit 222 generates monotone image data based on the lightness conversion formula set as shown in FIG.

  Thus, in this embodiment, the brightness conversion formula can be automatically adjusted according to the shooting mode information. As a result, it is possible to perform monotone processing suitable for the shooting mode.

G. Variations:
The present invention is not limited to the above-described examples and embodiments, and can be implemented in various modes without departing from the gist thereof. For example, the following modifications are possible.

G1. Modification 1:
A data processing unit including the image data analysis unit 226 illustrated in FIG. 2 and the shooting mode information analysis unit 228 illustrated in FIG. 9 may be used. In this case, if the image data file stores the shooting mode information INF, the monotone processing based on the shooting mode is performed. If the shooting mode information INF is not stored, the image data is analyzed. It is possible to adopt a configuration for performing a monotone processing based on the above. According to this configuration, it is possible to perform monotone processing suitable for color image data regardless of the presence or absence of shooting mode information. Further, when the shooting mode is the standard mode, a monotone process based on the result of analyzing the image data may be performed.

G2. Modification 2:
In each of the above-described embodiments, the characteristic color is determined based on the hue range, but may be determined by providing a range for saturation and lightness. In this way, the characteristic color can more appropriately reflect the color representing the characteristic of the subject.

G3. Modification 3:
In each of the above-described embodiments, the feature color information representing the pixel ratio is used as the color distribution information. However, the color distribution information is not limited to the feature color information, and is generally information related to the color deviation in the color image data. If it is. For example, a hue having a peak in the hue distribution may be used as the color distribution information, and the brightness conversion formula may be adjusted so that the brightness of the color having the hue becomes dark. Conversely, the brightness conversion formula may be adjusted so that the brightness of the color having the peak hue in the hue distribution becomes brighter.

G4. Modification 4:
The monotone image data generated by the monotone process is not limited to printing and can be used for various purposes. For example, it may be used for outputting an image to an LCD display or a CRT monitor, or an image data file for storing monotone image data may be generated. If such an image data file is generated and reused, a monotone image can be used even when using an apparatus that cannot execute monotone processing.

G5. Modification 5:
In each of the above-described embodiments, a computer is used as an image processing apparatus that executes monotone processing. Alternatively, the image output apparatus may be configured to execute monotone processing. For example, the control circuit (not shown) of the printer 300 (FIG. 1) can have a function as the data processing unit 220 and the print data generation unit 240. Furthermore, if the printer 300 is configured to receive image data directly from the digital camera 100 via a cable, wireless communication, a memory card MC, or the like, a monotone image can be printed without using the computer 200. Therefore, the user can easily use a high-quality monotone image.

G6. Modification 6:
In this specification, “digital camera” includes both a digital still camera that captures still images and a digital video camera that captures moving images.

G7. Modification 7:
In each of the above embodiments, a part of the configuration realized by software may be replaced by hardware, and conversely, a part of the configuration realized by hardware may be replaced by software. . For example, a part of the functions of the computer 200 (FIG. 2) can be executed by a control circuit (not shown) in the printer 300.

G8. Modification 8:
In each of the above embodiments, the image data and the image data related information need not be stored in the same image data file. Generally, an image data set in which image data and image data related information are associated with each other may be configured.

It is explanatory drawing which shows the structure of an image output system. 2 is a block diagram showing a configuration of a computer 200. FIG. It is explanatory drawing explaining the characteristic color information produced | generated by analyzing color image data. It is explanatory drawing explaining adjustment of a brightness conversion type | formula. It is explanatory drawing which shows the example of a monotone image. It is explanatory drawing explaining adjustment of a brightness conversion type | formula. It is explanatory drawing which shows a mode that a some lightness conversion type | formula is applied with respect to one color image data. It is explanatory drawing which shows the structure of image data file IDF. It is a block diagram which shows the structure of the computer 200a. It is explanatory drawing which shows a lightness conversion formula.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 ... Digital camera 200, 200a ... Computer 220, 220a ... Data processing part 222 ... Lightness conversion part 224, 224a ... Lightness conversion type adjustment part 226 ... Image data analysis part 228. ..Shooting mode information analysis unit 240 ... Print data generation unit 300 ... Printer IDF ... Image data file INF ... Shooting mode information IMG ... Color image data MC ... Memory card

Claims (7)

An image processing apparatus,
An image data analysis unit for analyzing color image data;
A data processing unit for converting the color image data into monotone image data;
With
The luminance value Y of the monotone image data is based on a ratio of the number of pixels having a specific hue included in the color image data to the number of pixels of the color image data .
Y = (kr_std + Δkr) × R + (kg_std + Δkg) × G + (kb_std + Δkb) × B
Determined by the formula
In the above formula,
R, G, and B are red, green, and blue pixel values of the pixels of the color image data expressed in RGB color space,
kr_std, kg_std, and kb_std are fixed values determined based on a conversion formula from the pixel values R, G, and B in the RGB color space to the luminance value Y in the YCbCr color space.
Δkr, Δkg, and Δkb are all set to 0 when the ratio of the number of pixels is equal to or less than a threshold value, and color is determined by photographing when the ratio of the number of pixels is greater than the threshold value. An image processing apparatus that is an adjustment value in which at least one is set to a value other than 0 in accordance with a shooting mode when the image data is generated and the specific hue . The image processing apparatus according to claim 1,
When the specific hue is sky blue, the luminance value of the pixel of the monotone image data corresponding to the pixel that showed a red hue in the color image data is the color image data when the specific hue is standard. Is determined to be larger than the luminance value of the pixel of the monotone image data corresponding to the pixel showing the red hue at
Image processing device. The image processing apparatus according to claim 1, wherein
In the case where the specific hue is sky blue, the luminance value of the pixel of the monotone image data corresponding to the pixel showing the blue hue in the color image data is the color image data when the specific hue is standard. Is determined to be smaller than the luminance value of the pixel of the monotone image data corresponding to the pixel showing the blue hue at
Image processing device. The image processing apparatus according to any one of claims 1 to 3,
When the specific hue is sky blue, the luminance value of the pixel of the monotone image data corresponding to the pixel that showed a green hue in the color image data is the color image data when the specific hue is standard. Determined to be smaller than the luminance value of the pixel of the monotone image data corresponding to the pixel showing the green hue at
Image processing device. The image processing apparatus according to any one of claims 2 to 4,
The image data analysis unit
Among the pixels of the color image data, as a pixel having the specific hue, when the ratio of the pixel hue H is in the color of the pixel in the range of 230 degrees to 260 degrees, greater than the threshold value Determines the specific hue as sky blue,
An image processing apparatus that determines the specific hue as a standard when the ratio is equal to or less than the threshold value. An image processing method comprising:
(A) analyzing color image data;
(B) converting the color image data into monotone image data,
The step (b)
The luminance value Y of the monotone image data is based on the ratio of the number of pixels having a specific hue included in the color image data to the number of pixels of the color image data .
Y = (kr_std + Δkr) × R + (kg_std + Δkg) × G + (kb_std + Δkb) × B
Viewing including the step of determining by the formula,
In the above formula,
R, G, and B are red, green, and blue pixel values of the pixels of the color image data expressed in RGB color space,
kr_std, kg_std, and kb_std are fixed values determined based on a conversion formula from the pixel values R, G, and B in the RGB color space to the luminance value Y in the YCbCr color space.
Δkr, Δkg, and Δkb are all set to 0 when the ratio of the number of pixels is equal to or less than a threshold value, and color is determined by photographing when the ratio of the number of pixels is greater than the threshold value. An image processing method , which is an adjustment value in which at least one is set to a value other than 0 according to a shooting mode when the image data is generated and the specific hue . A computer program for causing a computer to perform image processing,
A function to analyze color image data;
A function of converting the color image data into monotone image data;
The function of converting the color image data is
The luminance value Y of the monotone image data is based on the ratio of the number of pixels having a specific hue included in the color image data to the number of pixels of the color image data.
Y = (kr_std + Δkr) × R + (kg_std + Δkg) × G + (kb_std + Δkb) × B
Only contains a function that is determined by the formula,
In the above formula,
R, G, and B are red, green, and blue pixel values of the pixels of the color image data expressed in RGB color space,
kr_std, kg_std, and kb_std are fixed values determined based on a conversion formula from the pixel values R, G, and B in the RGB color space to the luminance value Y in the YCbCr color space.
Δkr, Δkg, and Δkb are all set to 0 when the ratio of the number of pixels is equal to or less than a threshold value, and color is determined by photographing when the ratio of the number of pixels is greater than the threshold value. A computer program which is an adjustment value in which at least one is set to a value other than 0 in accordance with a shooting mode when the image data is generated and the specific hue .

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