JP2010258703A - Information processor and information processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To properly reproduce an input image by a device. <P>SOLUTION: An information processor (101) performs conversion from color information relying on the device into color information without relying on the device concerning input image data, calculates chromaticity data of the input image data, based on the color information without relying on the device related to the converted input image data, corrects chromaticity data, while holding color temperature corresponding to the calculated chromaticity data, and then, corrects the input image data, based on the corrected chromaticity data. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to an information processing apparatus and an information processing method, and is particularly suitable for use in color reproduction of an input image.

  Conventionally, image processing called white balance processing is generally performed as processing for correcting an image taken with a video camera, digital camera, or the like so that the color of the image becomes more natural. The white balance processing is generally image processing for adjusting the balance of signal values of R / G / B components of image data. For example, in the white balance processing, image data is analyzed, the color deviation of the image highlight portion is detected, and the ratio of the signal values of the R / G / B components of the image highlight portion is 1: 1: 1. Thus, the balance of the signal values of the R / G / B components is relatively adjusted.

In recent years, as white balance processing, an image processing method has been proposed in which the degree of white balance correction is adjusted in accordance with the color deviation of an image highlight portion to correct image data (see Patent Document 1).
Here, the color temperature will be described in relation to the white balance. The color temperature corresponds to the color of the emitted light emitted from the complete black body when the complete black body is heated, and the color and temperature are related one-to-one, and as the temperature of the complete black body increases. The chromaticity changes from red to white and further to blue. For this reason, the expression “color temperature is low” when the redness of the entire image is strong, and “color temperature is high” when the blueness of the entire image is strong.
Note that when adjusting the white balance of an image shot with a digital camera, the white balance is adjusted by adjusting the color temperature in addition to adjusting the balance of the signal values of the R / G / B components. Can be done. For example, when the captured image is very reddish, it can be reddish by adjusting the color temperature high.

Japanese Patent Laid-Open No. 11-317959

However, in the conventional method of adjusting the white balance of the image by the color temperature, the reddish-blued direction can be adjusted, but cannot be adjusted in the green direction away from the black body radiation locus. In addition, since it is difficult to adjust only the green component while maintaining the color temperature, a great deal of effort is required to adjust the color when trying to adjust the green component based on the balance of the R / G / B component signal values. It becomes.
In the technique disclosed in Patent Document 1, white balance is calculated by calculating white balance from RGB data of image data. However, characteristics of a device that actually reproduces image data are not considered. For this reason, the problem that an image is not suitably reproduced by the use environment of image data may arise.

  The present invention has been made in view of such problems, and an object thereof is to appropriately reproduce an input image by a device.

  Therefore, the present invention provides an information processing apparatus that does not depend on a conversion unit that performs conversion from color information that depends on a device to color information that does not depend on the device for input image data, and the device that is converted by the conversion unit. Calculation means for calculating chromaticity data of the input image data based on color information, and correction means for correcting the chromaticity data while maintaining a color temperature corresponding to the chromaticity data calculated by the calculation means And image correction means for correcting the input image data based on the chromaticity data corrected by the correction means.

  According to the present invention, it is possible to appropriately reproduce an input image by a device.

It is a figure which shows the structure of information processing apparatus. It is a figure which shows the flow of the exemplary process in an information processing apparatus. It is a figure which shows the example of the file format which a device characteristic acquisition part acquires. It is a figure which shows the flow of the exemplary process in an image data analysis part. It is a figure which shows the example of the histogram produced by the image data analysis part. It is a figure which shows the flow of the exemplary process in a white balance calculation part. It is a figure which shows the flow of the exemplary process in a white balance correction | amendment part. It is a figure which shows the flow of the exemplary process in an image conversion process part. It is a figure which shows an observation environment parameter. It is a figure which shows the structure of the information processing apparatus of 2nd Embodiment. It is a figure which shows the flow of the exemplary process in the information processing apparatus of 2nd Embodiment. It is a figure which shows the flow of the exemplary process in the white balance calculation part of 2nd Embodiment. It is a figure which shows the example of UI displayed to a user in order to adjust the color of an image. It is a figure which shows the flow of the exemplary process in the white balance correction | amendment part of 3rd Embodiment. It is a figure which illustrates the chromaticity data of white balance adjustment.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

(First embodiment)
FIG. 1 is a diagram showing a configuration of an information processing apparatus 101 according to the first embodiment of the present invention. First, the hardware configuration of the information processing apparatus 101 will be described with reference to FIG.

The information processing apparatus 101 includes a CPU (Central Processing Unit) 1 and a storage device 2. Note that the devices included in the information processing device 101 are configured to be communicable with each other and are connected by a bus or the like. The CPU 1 controls the operation of the information processing apparatus 101 and executes a program stored in the storage device 2. The storage device 2 is a storage device such as a magnetic storage device or a semiconductor memory, and stores a program read based on the operation of the CPU 1, data that must be stored for a long time, and the like. In the present embodiment, the CPU 1 performs processing according to the procedure of the program stored in the storage device 2, thereby realizing functions in the information processing apparatus 101 and processing according to flowcharts described later.
Note that the hardware configuration of the information processing apparatus 101 is not limited to the above-described configuration. For example, the information processing apparatus 101 may include input devices such as a mouse, a keyboard, a touch panel device, and buttons for inputting various instructions. Further, for example, the information processing apparatus 101 may include an output device such as a liquid crystal panel or an external monitor that outputs various types of information. For example, the information processing apparatus 101 may include an I / O device for performing communication between various devices. The I / O device is a memory card, an input / output unit such as a USB cable, a transmission / reception unit by wire, wireless, or the like.

  Next, the functional configuration of the information processing apparatus 101 will be described with reference to FIG. The information processing apparatus 101 includes an image data acquisition unit 103, a device characteristic acquisition unit 105, an image data analysis unit 106, a UI unit 107, a projection unit 108, a white balance calculation unit 109, a white balance correction unit 110, and an image conversion processing unit 111. It is comprised including.

The image data acquisition unit 103 acquires RGB image data that is conversion source image data from the image data holding device 102 that holds RGB image data that is conversion source image data (in other words, input image data). The device characteristic acquisition unit 105 acquires device characteristic data from the device characteristic holding device 104 that holds the device characteristic data. The image data analysis unit 106 analyzes the RGB image data. The UI unit 107 outputs a UI (user interface) to an output device (not shown) such as a display device. The projection unit 108 outputs the RGB image data subjected to the image conversion process to an output device, and projects it on a screen (not shown). The white balance calculation unit 109 calculates the white balance of the RGB image data. The white balance correction unit 110 corrects the white balance. The image conversion processing unit 111 converts RGB image data using a color perception model. The buffer memory unit 112 is a storage area provided in the storage device 2 and temporarily stores image data, calculation results, and the like for performing calculation processing.
The information processing apparatus 101 may include one or both of the image data holding apparatus 102 and the device characteristic holding apparatus 104.

<Operation in Information Processing Apparatus 101>
FIG. 2 is a diagram illustrating an example of a flowchart relating to processing executed by the information processing apparatus 101. Note that the processing according to the following flowchart is realized by the CPU 1 included in the information processing apparatus 101 executing a control program stored in the storage device 2 or the like.

In step S <b> 1, the image data acquisition unit 103 acquires RGB image data that is conversion source image data from the image data holding device 102, and stores the acquired RGB image data in the buffer memory unit 112.
In step S2, the image data analysis unit 106 analyzes the RGB image data acquired in step S1, and creates a histogram of the RGB image data. Specific processing of the image data analysis unit 106 will be described later.

  In step S <b> 3, the device characteristic acquisition unit 105 acquires device characteristic data from the device characteristic holding device 104. Device characteristic data is a file in which conversion characteristics from device-dependent color (RGB), which is color information depending on the device (projector, etc.), to device-independent color (XYZ), which is color information independent of the device, are associated with each other. (Characteristic information). The conversion characteristics are described as, for example, a γ + 3 × 3 conversion matrix from RGB to XYZ, or a conversion lookup table (LUT). In the present embodiment, an LUT is used, and for example, the correspondence between RGB values arranged in uniform grid points and XYZ values is described in the LUT as in the format shown in FIG. 3, and tetrahedral interpolation is performed based on this correspondence. The RGB values are converted into XYZ values by performing the same. Note that the LUT data employed in the present embodiment is a value obtained by measuring the projected color of a device in a dark environment.

In step S4, the white balance calculation unit 109, which is an example of a conversion unit and a calculation unit, calculates white balance based on the histogram of the RGB image data acquired in step S2 and the device characteristic data acquired in step S3. . A specific process in which the white balance calculation unit 109 calculates white balance (in other words, chromaticity data of RGB image data) will be described later.
In step S5, the white balance correction unit 110, which is an example of a correction unit, corrects the white balance using the white balance and black body radiation locus data calculated in step S4. Note that specific processing of the white balance correction unit 110 will be described later.

In step S6, the image conversion processing unit 111, which is an example of an image correction unit, corrects the RGB image data using the white balance corrected in step S5. Note that specific processing of the image conversion processing unit 111 will be described later.
In step S <b> 7, the projection unit 108 projects the RGB image data corrected in step S <b> 6 on the screen and ends the process.

  Note that the procedure performed by the information processing apparatus 101 is not limited to this. For example, the process of step S3 may be performed before the process of step S1, and the procedure in which the information processing apparatus 101 performs the process can be changed as appropriate.

<Operation of Image Data Analysis Unit 106>
FIG. 4 is a diagram illustrating an example of a flowchart relating to specific processing of the image data analysis unit 106 in step S2.

In step S <b> 21, the image data analysis unit 106 acquires RGB image data for one pixel from the buffer memory unit 112, and stores the RGB values of the acquired RGB image data in a histogram holding unit (not shown) provided in the buffer memory unit 112. ).
In step S22, the image data analysis unit 106 updates the histogram held in the histogram holding unit based on the RGB values of the RGB image data acquired in step S21. In the histogram holding unit, HistR [R], HistG [G], and HistB [B] for storing signal values (RGB values) of R / G / B components, and appearance frequencies of pixels having the signal values The relationship is held as a histogram. The initial states of HistR [R], HistG [G], and HistB [B] are all 0. The histogram is updated according to the following equation (a).

In step S23, the image data analysis unit 106 determines whether or not the histogram update has been completed for all the pixels of the RGB image data. If all the histograms have been updated, the process of step S24 is performed. On the other hand, when the update of all the histograms has not been completed, the image data analysis unit 106 returns the process to step S21 and continues the process again.
In step S24, the image data analysis unit 106 stores the histogram created in step S23 in the buffer memory unit 112. FIG. 5 illustrates the histogram created in step S2.

<Operation of White Balance Calculation Unit 109>
FIG. 6 is a diagram illustrating an example of a flowchart relating to specific processing of the white balance calculation unit 109 in step S4.

In step S <b> 41, the white balance calculation unit 109 acquires the histogram of the RGB image data created in step S <b> 2 from the buffer memory unit 112.
In step S42, the white balance calculation unit 109 acquires the signal value of each R / G / B component having the highest appearance frequency in the highlight area of the histogram acquired in step S41 as an RGB value to be used for white balance correction. To do. The highlight area of the histogram means, for example, an area 5% above HistR [R], HistG [G], and HistB [B] in the histogram.

  In step S43, the white balance calculation unit 109 converts the RGB value acquired in step S42 into chromaticity data based on the device characteristics acquired in step S2. The chromaticity data (xy chromaticity value) is calculated according to the following formula (b) using the XYZ value by converting the RGB value acquired in step S42 into an XYZ value based on the device characteristics.

  In step S44, the white balance calculation unit 109 stores the chromaticity data calculated in step S43 in the buffer memory unit 112.

<Operation of White Balance Correction Unit 110>
FIG. 7 is a diagram illustrating an example of a flowchart relating to specific processing of the white balance correction unit 110 in step S5.

In step S51, the white balance correction unit 110 acquires the chromaticity data calculated in step S4 from the buffer memory unit 112.
In step S52, the white balance correction unit 110 calculates the correlated color temperature (T) in the chromaticity data acquired in step S51 using the following equation (c).

  In step S53, the white balance correction unit 110 calculates chromaticity data on the black body radiation locus corresponding to the correlated color temperature calculated in step S52 using the following equation (d). As described above, the chromaticity data at the intersection of the correlated color temperature line represented by the locus of chromaticity data for the correlated color temperature equal to the correlated color temperature calculated in step S52 and the black body radiation locus is obtained here. I am doing so. However, this is not always necessary. For example, when the chromaticity data calculated in step S4 is away from the black body radiation locus, the white balance correction unit 110 is on or close to the black body radiation locus along the correlated color temperature line. The chromaticity data may be corrected in the direction. That is, in a broad sense, the white balance correction unit 110 corrects the chromaticity data in a state where the color temperature corresponding to the chromaticity data is kept constant.

  In step S54, the white balance correction unit 110 stores the chromaticity data calculated in step S53 in the buffer memory unit 112.

<Operation of Image Conversion Processing Unit 111>
FIG. 8 is a diagram illustrating an example of a flowchart relating to specific processing of the operation of the image conversion processing unit 111 in step S6.

In step S <b> 61, the image conversion processing unit 111 acquires an RBG value of RGB image data for one pixel from the buffer memory unit 112.
In step S62, the image conversion processing unit 111 acquires device characteristic data from the buffer memory unit 112, and converts the RGB values of the RGB image data into XYZ values based on the device characteristic data.
In step S63, the image conversion processing unit 111 converts the XYZ values into perceptual color data using the forward appearance model. A specific conversion formula will be described later. For the observation environment parameters necessary for the conversion formula, the chromaticity data calculated in step S4 is set for the white point, and the recommended parameters of CIECAM02 are set for the other parameters.

In step S64, the image conversion processing unit 111 converts the perceptual color data calculated in step S63 into an X′Y′Z ′ value using the reverse appearance model. As for the observation environment parameters necessary for the conversion formula, the chromaticity data corrected in step S5 is set for the white point, and the recommended parameters of CIECAM02 are set for the other parameters.
In step S65, the image conversion processing unit 111 acquires device characteristic data from the buffer memory unit 112, and converts the X′Y′Z ′ value calculated in step S64 based on the device characteristic data into an R′G′B ′ value. Convert.

In step S66, the image conversion processing unit 111 determines whether or not the image conversion has been completed for all the pixels. If all the image conversions have been completed, the processing ends. On the other hand, if all image conversions have not been completed, the image conversion processing unit 111 returns the processing to step S61 and continues the processing.
In step S 67, the image conversion processing unit 111 stores the R′G′B ′ value converted in steps S 61 to S 66 in the buffer memory unit 112.
In other words, the image conversion processing unit 111 applies a perceptual model using the corrected chromaticity data as a parameter, and calculates an X′Y′Z ′ value (color information independent of the device) related to the RGB image data. The image conversion processing unit 111 then converts the X′Y′Z ′ value to the R′G corresponding to the X′Y′Z ′ value for all the calculated X′Y′Z ′ values based on the device characteristic data. The RGB image data is corrected by converting it to a 'B' value (color information depending on the device).

Here, the transformation model of the appearance model (CIECAM02) and the observation condition parameters of the appearance model will be described.
<Conversion formula of appearance model (CIECAM02)>
The processing flow in CIECAM02 (forward conversion) will be described by dividing it into three conversion units: a color adaptation unit, a cone response unit, and a psychological value conversion unit.
In the chromatic adaptation unit, the XYZ value is converted into the spectral sensitivity of the cone by the equation (1), and the signal of each cone is normalized by the white point value of the light source by the equation (3). The adaptation coefficient D is calculated by equation (4). Finally, the equation (2) is used to convert the value into an XYZ value corresponding to the light source under the observation environment.

  In the cone response unit, the XYZ value is converted into the spectral sensitivity of the cone by the equation (5), and converted into a cone response value after adaptation according to the intensity of the amount of light entering the eye by the equation (6).

  The psychological value conversion unit converts the cone response value into signal values of an achromatic color response and an opposite color response in the visual cortex using the equations (7), (8), and (9), and this signal value is converted into the signal value. Using the equations (10), (11), and (12), conversion into perceptual lightness J value, perceptual saturation C value, and perceptual hue h value is performed.

  The CIECAM02 inverse conversion unit sets the observation condition parameters according to the observation environment, newly calculates the achromatic response Aw in the forward conversion process, and performs the reverse process of the forward conversion unit from the Aw, JCh value, and such coefficients. Thus, the perceptual color data is converted into XYZ values.

<Observation condition parameters of color perception model (CIECAM02)>
FIG. 9 is a diagram showing observation condition parameters recommended in CIECAM02. The ambient condition average shown in FIG. 9 indicates an average periphery (peripheral relative luminance is 20% or more of white in the target scene). The surrounding condition dim indicates a dim surrounding (the relative luminance of the surrounding is 20% or less of white in the target scene). The ambient condition dark indicates a dark periphery (the relative luminance of the periphery is 0% of white in the target scene). In this embodiment, the XYZ value based on the chromaticity data calculated in step S4 is used for white at the time of forward conversion, and the XYZ value based on chromaticity data calculated at step S5 is used for the white at the time of reverse conversion. For other parameters, use the recommended parameters of CIECAM02.

<Example of effects of first embodiment>
The information processing apparatus 101 according to the present embodiment analyzes image information of an input image, calculates white balance in association with device characteristics, and corrects the white balance on a black body radiation locus according to a correlated color temperature line. According to this configuration, it is possible to correct the white balance while maintaining the color temperature corresponding to the input image, that is, to easily adjust the color tone as compared with the conventional case, and in addition, the device is actually used. It is possible to reproduce a suitable image in the scene to be viewed.

(Second Embodiment)
In the second embodiment, in addition to the processing of the first embodiment, processing for correcting white balance is performed in consideration of the influence of illumination light reflected on the projection surface. Therefore, in the present embodiment, differences from the first embodiment, such as a change point provided with a unit that acquires illumination light, will be described.

  FIG. 10 is a diagram illustrating a configuration of the information processing apparatus 101 according to the second embodiment. In FIG. 10, the same reference numerals as those in FIG. 1 are assigned to the same parts as those of the information processing apparatus 101 according to the first embodiment. As illustrated in FIG. 10, the information processing apparatus 101 according to the second embodiment is different from the information processing apparatus 101 according to the first embodiment in that an illumination data acquisition unit 114 is provided. The illumination data acquisition unit 114 acquires illumination data from the measuring instrument 113 that measures illumination data. Note that a configuration in which the information processing apparatus 101 includes the measuring device 113 may be employed.

<Operation in Information Processing Apparatus 101>
FIG. 11 is a diagram illustrating an example of a flowchart relating to processing executed by the information processing apparatus 101. With reference to FIG. 11, the process of step S14 and step S15 which are processes peculiar to 2nd Embodiment is demonstrated. The other processes from step S11 to S13 and the processes from step S16 to S18 are respectively the processes from step S1 to S3 in FIG. 2 described in the first embodiment and the processes from step S5 to S7. Since it is the same as the process, the description is omitted.

  In step S <b> 14, the illumination data acquisition unit 114 measures the XYZ values of the projection plane using the measuring device 113. Note that a black (reference color) color chart with R = 0, G = 0, and B = 0 is displayed for measurement on the projection surface, and is projected in an environment where an image (that is, reference image data) is actually viewed. The XYZ value of the surface is measured.

  In step S15, the white balance calculation unit 109 calculates the white balance. That is, the white balance calculation unit 109 uses the histogram of the RGB image data acquired in step S12, the device characteristic data acquired in step S13, and the amount of reflected illumination light based on the value measured in step S14. Is calculated. Specific processing of the white balance calculation unit 109 will be described later.

<Operation in White Balance Calculation Unit 109>
FIG. 12 is a diagram illustrating a flowchart relating to specific processing of the white balance calculation unit 109, which is an example of a calculation unit in step S15. With reference to FIG. 12, the process from step S153 to step S155 which is a process peculiar to 2nd Embodiment is demonstrated. The other processes in steps S151, S152, and S156 are the same as the processes in steps S41, S42, and S44 of FIG. 6 described in the first embodiment, and thus description thereof is omitted.

In step S153, the white balance calculation unit 109 converts the RGB values calculated in step S152 into XYZ values based on the device characteristics acquired in step S13.
In step S154, the white balance calculation unit 109 corresponds to the measurement values (XL, YL, BL) measured in step S14 and the device characteristic data (R = 0, G = 0, B = 0) acquired in step S13. XYZ values (XB, YB, ZB) are acquired. Then, the white balance calculation unit 109 calculates the amount of illumination light reflected (XS, YS, ZS) based on the acquired value by the following equation (e).

  In step S155, the white balance calculation unit 109 calculates chromaticity data by adding the amount of reflection calculated in step S154 to the XYZ value converted in step S153. That is, the white balance calculation unit 109 calculates chromaticity data adapted to illumination in an environment where input image data (here, RGB image data) is used in the device.

<Example of effect of second embodiment>
As described above, the information processing apparatus 101 according to the present embodiment analyzes the image information of the input image, calculates the white balance in association with the device characteristics and the illumination light, and corrects the white balance on the black body radiation locus according to the correlated color temperature line. To do. According to this configuration, since it is possible to calculate the white balance in consideration of the amount of reflected illumination light, in addition to the effects described in the first embodiment, (only the scene that is actually viewed using the device) In addition, there is an effect that a suitable image can be reproduced even in a visual environment.

(Third embodiment)
In the third embodiment, in addition to the configuration according to the first embodiment or the configuration according to the second embodiment, the UI for adjusting the white balance is displayed to the user, and the white balance is obtained from the adjustment value acquired by the UI. Adopt a configuration to correct. Therefore, in the present embodiment, a method for acquiring a white balance adjustment value by the UI unit 107 and a processing method for correcting the white balance using the acquired white balance adjustment value, which are differences from the first embodiment (FIG. 2). Step S5) will be described.

First, a method by which the UI unit 107 acquires a white balance adjustment value will be described with reference to FIG.
The UI unit 107 displays a UI having a color adjustment bar as shown in FIG. 13 on an output device or the like. The user can control the color of the display image by operating the color adjustment bar via an input device or the like. The color adjustment bar internally indicates a numerical value within a range of 0 to 1 with a predetermined value (for example, in increments of 0.2). The UI unit 107 corresponds to a value of 1 when no correction is selected by the color adjustment bar in FIG. 13, a value of 0 when neutral is selected, and a step size when the interval is selected. Value to be acquired as a white balance adjustment value.

  Next, with reference to FIG. 14, processing for correcting white balance based on a white balance adjustment value acquired by a user operation of the UI unit 107 will be described. FIG. 14 is a diagram illustrating an example of a flowchart relating to processing for correcting white balance. Here, the processes in steps S74 and S75, which are processes unique to the third embodiment, will be described. The other processes from step S71 to step S73 and step S76 are the same as the processes from step S51 to step S53 of FIG. 7 and step S54 described in the first embodiment, respectively. Omitted.

In step S <b> 74, the white balance correction unit 110 acquires a white balance adjustment value from the UI unit 107.
In step S75, the white balance correction unit 110 converts the chromaticity data acquired in step S71 and the chromaticity data acquired in step S73 into uv chromaticity values closer to human senses. The white balance correction unit 110 associates the chromaticity data acquired in step S71 with no correction and the chromaticity data acquired in step S73 with neutral. The white balance correction unit 110 adds and averages the uv chromaticity values using the white balance adjustment value acquired in step S74 as an internal dividing point. Further, the white balance correction unit 110 converts the uv chromaticity value after calculation into chromaticity data again. The uv chromaticity value is calculated by the following equation (f).
Here, FIG. 15 shows an example of adjustment of chromaticity data. In FIG. 15, 151 is a black body radiation locus (3000K-1200K). Reference numeral 152 denotes a correlated color temperature line. Reference numeral 153 denotes white balance (chromaticity data) calculated from RGB image data (input image data). Reference numeral 154 denotes chromaticity data at a color temperature corresponding to the chromaticity data of the RGB image data (in other words, chromaticity data on the black body radiation locus 151 related to the input image data). Reference numeral 155 denotes chromaticity data calculated by the internal ratio set by the UI unit 107.

<Example of effect of third embodiment>
The information processing apparatus 101 according to the present embodiment has a mechanism that can easily adjust the white balance to a neutral chromaticity value when the user adjusts the color of an image. According to this mechanism, in addition to the effects described in the first embodiment, it is possible to reduce annoyance that cannot be color-corrected faithfully to the color temperature of the content for the white balance, and to reduce the burden of the user's adjustment work.

(Modification)
<Image data analysis unit>
In the information processing apparatus according to each embodiment, a histogram is created and white balance processing is performed as an RGB image data analysis unit, but the white balance processing is not limited thereto. For example, in the white balance process, a scene distribution may be determined by analyzing the color distribution of the histogram, and a process for separating an image that should be subjected to the white balance process and an image that should not be performed may be performed. According to this configuration, by adjusting the white balance uniformly in any scene, it is possible to avoid the situation where the image becomes unnatural depending on the scene.

<Histogram calculation method>
In the information processing apparatus according to each embodiment, the mode value in the upper 5% of the histogram is used when acquiring the RGB value from the highlight area of the histogram, but the process of acquiring the RGB value from the histogram is It is not limited. For example, in the process of acquiring RGB values from the histogram, the average value in the upper 5% of the histogram, the maximum value of the histogram, or the like may be used. Further, in the process of acquiring RGB values from the histogram, a method may be used in which a threshold value is provided in the histogram and the average value, mode value, etc. in the upper 1% of the histogram above or below the threshold value are used as the RGB value.

<White balance correction method>
In the information processing apparatus according to each embodiment, the white balance correction unit 110 calculates the white balance of the RGB image data and corrects the white balance into chromaticity data on the black body radiation locus. However, the process of correcting is not limited to this. For example, a configuration in which an allowable range along the black body radiation locus is provided and the white balance correction unit 110 corrects if the white balance is outside the allowable range and does not correct if the white balance is within the allowable range may be employed.

<Image conversion processing method>
In the information processing apparatus according to each embodiment, the RGB image data is converted from the RGB value to the R′G′B ′ value using an appearance model, but the RGB value is converted into the R′G′B ′ value. However, the conversion process is not limited to this. For example, this conversion processing may be performed by LUT processing using RGB values at a certain grid point. Also, without using the appearance model, a white balance correction coefficient is simply calculated from the RGB value before white correction and the R′G′B ′ value after correction, and the RGB image data is converted using this coefficient. A configuration for converting RGB values may be employed. As coefficients, for example, Rk = R ′ / R, Gk = G ′ / G, and Bk = B ′ / B are adopted.

<Black body radiation locus data>
In the information processing apparatus according to each embodiment, the chromaticity data on the blackbody radiation locus is calculated using the equation (d). It is not limited. For example, the chromaticity data is calculated in advance for a predetermined correlated color temperature, the correspondence relationship between the correlated color temperature and the chromaticity data is stored as a table, and the chromaticity data calculation process of the black body radiation locus is referred to by referring to this You may employ | adopt the structure to perform.

<UI in the Third Embodiment>
In the information processing apparatus according to the third embodiment, a UI is used for image adjustment, but the UI is not limited to this. For example, you may employ | adopt the structure used together with UI which can adjust the color temperature along the black-body radiation locus of a blue-red direction.

<Information processing device>
This information processing apparatus may be applied to a system constituted by a plurality of devices (host computer, interface device, reader, display, etc.) or may be applied to an apparatus (projector, etc.) constituted by one device.

<Storage medium>
As a storage medium for supplying the program code, a flexible disk, hard disk, optical disk, magneto-optical disk, CD-ROM, CD-R, magnetic tape, nonvolatile memory card, ROM, or the like can be used.

<Other embodiments>
The object of the above-described embodiment is achieved by the following. That is, a storage medium (or recording medium) in which a program code of software that realizes the functions of the above-described embodiments is recorded is supplied to the system or apparatus. Then, the central processing unit (CPU or MPU) of the system or apparatus reads and executes the program code stored in the storage medium. In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiment, and the storage medium recording the program code constitutes the above-described embodiment.

  In addition, by executing the program code read by the central processing unit of the system or apparatus, an operating system (OS) or the like operating on the system or apparatus performs actual processing based on an instruction of the program code. Do some or all. The case where the function of the above-described embodiment is realized by the processing is also included.

  Furthermore, it is assumed that the program code read from the storage medium is written to a memory provided in a function expansion card inserted into the system or apparatus or a function expansion unit connected thereto. After that, based on the instruction of the program code, the CPU of the function expansion card or function expansion unit performs part or all of the actual processing, and the function of the above-described embodiment is realized by the processing. It is.

  When the above-described embodiment is applied to the storage medium, the storage medium stores program codes corresponding to the flowcharts described above.

  In the above-described embodiment, for example, based on the image information of the input image, white balance is calculated in association with device characteristics, illumination light, etc., and the calculated white balance is calculated along the correlated color temperature line in the direction of the black body radiation locus. to correct. According to this configuration, it is possible to correct the white balance while maintaining the color temperature, and it is possible to reproduce a suitable image in a scene and an illumination environment that are actually viewed using a device. Moreover, according to this structure, the burden concerning the operation | work which adjusts colors, such as white balance correction | amendment by a user, can be reduced.

  The preferred embodiments of the present invention have been described in detail above, but the present invention is not limited to such specific embodiments, and various modifications can be made within the scope of the gist of the present invention described in the claims.・ Change is possible.

DESCRIPTION OF SYMBOLS 101 Information processing apparatus 103 Image data acquisition part 105 Device characteristic acquisition part 106 Image data analysis part 108 Projection part 109 White balance calculation part 110 White balance correction part 111 Image conversion process part 112 Buffer memory part

Claims (6)

Conversion means for converting input device data from device-dependent color information to device-independent color information; and
Calculation means for calculating chromaticity data of the input image data based on the color information independent of the device converted by the conversion means;
Correction means for correcting the chromaticity data while maintaining a color temperature corresponding to the chromaticity data calculated by the calculation means;
Image correcting means for correcting the input image data based on the chromaticity data corrected by the correcting means;
An information processing apparatus comprising:   When the chromaticity data calculated by the calculating unit is away from the black body radiation locus, the correction unit is arranged on the black body radiation locus or on the black body radiation line based on the correlated color temperature line related to the chromaticity data. The information processing apparatus according to claim 1, wherein the chromaticity data is corrected in a direction approaching a body radiation locus.   The image correction unit calculates chromaticity data of the input image data by applying a perceptual model using the chromaticity data corrected by the correction unit as a parameter, and based on the calculated chromaticity data, the input image The information processing apparatus according to claim 1, wherein the data is corrected. The converting means performs conversion from color information dependent on the device to color information independent of the device for reference image data,
The calculation means includes color information independent of the device measured when the reference image data is illuminated by the device, and color information independent of the device converted by the conversion means in the reference image data. The input amount adapted to the amount of illumination when the input image data is used in the device based on the calculated amount of reflection, and the amount of reflection reflected in the input image data is calculated using The information processing apparatus according to claim 1, wherein chromaticity data of an image is calculated. A conversion step for converting input device data from device-dependent color information to device-independent color information;
A calculation step of calculating chromaticity data of the input image data based on the device-independent color information converted in the conversion step;
A correction step of correcting the chromaticity data while maintaining a color temperature corresponding to the chromaticity data calculated in the calculation step;
An image correction step for correcting the input image data based on the chromaticity data corrected in the correction step;
An information processing method comprising: A conversion step for converting input device data from device-dependent color information to device-independent color information;
A calculation step of calculating chromaticity data of the input image data based on the device-independent color information converted in the conversion step;
A correction step of correcting the chromaticity data while maintaining a color temperature corresponding to the chromaticity data calculated in the calculation step;
An image correction step for correcting the input image data based on the chromaticity data corrected in the correction step;
A program that causes a computer to execute.

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