WO2012001949A1 - カラー画像処理方法、カラー画像処理装置およびカラー画像処理プログラム - Google Patents
カラー画像処理方法、カラー画像処理装置およびカラー画像処理プログラム Download PDFInfo
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Definitions
- the present invention relates to image processing for color images, and in particular, a color image processing method, color image processing apparatus, and color image processing for performing image processing for improving the texture of an object in a color image actually captured using a photographing device. Regarding the program.
- the color of a specific object for example, skin color, green of a plant, blue sky, etc.
- the color of a specific object for example, skin color, green of a plant, blue sky, etc.
- Various approaches have been proposed. By using such a method, it becomes possible to reproduce a preferable color.
- Patent Document 1 discloses a technique related to color correction of a color image.
- a representative color is extracted from an area to be corrected in an image, and the representative color is compared with a preset correction center color to determine an RGB correction parameter.
- Each pixel is corrected by controlling the application intensity of the correction parameter according to the distance between the pixel in the image and the center color.
- the hue, saturation, and brightness of each pixel are calculated from the RGB values that are the color information of each pixel. Then, the distance between the color of each pixel in the color space and the correction center color is calculated, and the correction intensity is adjusted according to the distance. In this way, the color of the object is intensively corrected.
- color correction based on addition / subtraction of correction parameters is performed in the RGB color space.
- the RGB correction amount is calculated for each pixel according to the distance from the correction center color.
- a correction parameter corresponding to the distance from the correction center color is added to or subtracted from the RGB value of each pixel in almost the entire face area.
- Patent Document 2 discloses a technique for detecting a face area in an input image.
- the eye detection method described in Patent Document 2 is a pair-of-eye evaluation value based on the features formed by both eyes even when the eyes are evaluated alone, even if the eyes cannot be distinguished from other parts due to insufficient features. By distinguishing between eyes and other parts.
- Patent Documents 3 to 5 describe techniques related to color image correction processing.
- the spectral color is converted to a lower-dimensional color space than the original dimension, color correction is performed in the lower-dimensional color space, and then the lower-dimensional color data is corrected.
- a color correction apparatus and method for generating spectral light of an appropriate dimension from spectral colors are disclosed.
- Patent Document 4 discloses a color conversion method for converting an original color space to a color of a target color space while matching the appearance of colors between color systems having different reference whites. Specifically, in the color conversion method described in Patent Document 4, the spectral distribution characteristics of the original reference white are restored from the color temperature of the original reference white, which is the reference white of the original color space. Further, the spectral distribution characteristic of the target reference white is restored from the color temperature of the target reference white which is the reference white of the target color space. Then, the surface reflectance of the arbitrary color in the original color space is restored using the tristimulus values in the arbitrary color, the light distribution characteristic of the original reference white, and the human color matching function. Further, tristimulus values that are colors in the target color space are obtained based on the restored surface reflectance, the restored spectral distribution characteristics of the target reference white, and the human color matching function.
- Patent Document 5 discloses a technique for automatically performing good color correction on important subjects in natural images taken under various lighting environments. Specifically, in the color correction method described in Patent Document 5, the body surface color of the specific object is extracted, and the color correction parameter optimum for the extracted representative color is set. Using this parameter, color correction conversion that only affects a specific hue is performed. By performing such conversion, it is possible to automatically perform color correction on an important subject in a natural image taken under various lighting environments.
- Patent Document 6 describes a technique of generating a facial skin reflection model and applying the model to rendering of a facial image.
- a three-dimensional shape obtained by scanning a face with a 3D scanner is acquired.
- a plurality of face images illuminated from different viewpoints with different illumination directions are acquired.
- the total reflectance and the normal map are estimated.
- the total reflectance is separated into two components, ie, subsurface scattering and (specular) surface reflectance, and the diffuse reflectance is estimated based on these two components.
- the subsurface reflectance is scanned using an optical fiber spectrometer to obtain a translucency map.
- Patent Document 7 pixel values of pixels constituting an image are separated into a surface reflected light component due to surface reflection and a diffuse reflected light component due to diffuse reflection in a three-dimensional object, and the surface reflected light component and diffuse reflected light are separated.
- An image processing method for changing at least one of the components is described.
- a reflection model hereinafter referred to as a clinker separation method
- Klinker et al. Is used to separate a reflection model into a surface reflection light component and a diffuse reflection light component.
- each separated reflection component is changed using a Phong illumination model, a Lambertian Reflection model, or the like.
- Non-Patent Document 1 describes a face detection method using generalized learning vector quantization.
- Non-Patent Document 2 describes a face detection method that combines an image-based type and a feature-based type that detects eyes using generalized learning vector quantization.
- the face information of the three-dimensional shape (three-dimensional information) is restored from the two-dimensional face image.
- the method of doing is also known (for example, nonpatent literature 3).
- Patent Documents 1 and 2 The matters described in Patent Documents 1 and 2 and the matters described in Non-Patent Documents 1 and 2 are appropriately cited in the embodiment of the present invention.
- Patent Document 1 achieves higher image quality by making the color of the object in the color image more desirable, but the texture is reduced. There was a problem that.
- Patent Document 6 it is proposed to apply a human skin reflex model to rendering of a face image.
- the method described in Patent Document 6 requires an optical fiber spectrometer that is a special measuring device in order to obtain three-dimensional information of a face image. For this reason, it is difficult to apply this method to color correction performed by a general color image processing apparatus.
- Non-Patent Document 3 it is also possible to use a restoration technique from a two-dimensional face image to a three-dimensional face image as a method for obtaining three-dimensional information of a face image.
- a restoration technique from a two-dimensional face image to a three-dimensional face image as a method for obtaining three-dimensional information of a face image.
- the calculation cost can be reduced more than the restoration technique described in Non-Patent Document 3. That is, it is desirable that color image processing can be performed without using the special measuring apparatus described above or a technique that requires high calculation costs.
- the image processing method described in Patent Document 7 does not restore the three-dimensional information of the object in the image, and applies a model related to illumination and reflection such as a clinker separation method, a phonillumination model, and a Lambertian reflection model. By doing so, the color is changed.
- the image processing method described in Patent Document 7 is an effective method when the assumed reflection models such as plastic, paint, paper, and ceramics are in good agreement.
- an image processing method described in Patent Document 7 is used to change an object having complicated reflection characteristics such as human skin, there is a problem that an artifact is generated. Therefore, in the image processing method described in Patent Document 7, it is difficult to say that the object can be reproduced in a desired color and the texture can be improved.
- Patent Document 7 does not disclose a method for correcting an object in an input image to a desired image quality.
- the present invention provides a color image processing method, a color image processing apparatus, and a color image processing program capable of improving the texture of an object in a color image photographed by a color image device at a low calculation cost. With the goal.
- the color image processing method detects an object area, which is an area targeted for image processing, from an input image, and calculates color information in the object area and a complete diffusion component that is a low-frequency component in the object area. Then, the surface reflection component is restored based on the color information and the low frequency component, and the restored surface reflection component is corrected according to the reference surface reflection component which is a surface reflection component preset according to the object region. A reproduction color that is a color obtained by correcting each pixel in the input image is calculated using the complete diffusion component and the corrected surface reflection component, and an output image is generated based on the reproduction color.
- the color image processing apparatus includes a target area detection unit that detects a target area that is a target area for image processing from an input image, color information in the target area, and low-frequency components in the target area.
- Reflection component restoration means that calculates a complete diffusion component and restores the surface reflection component based on the color information and the low frequency component, and a reference surface reflection component that is a surface reflection component preset according to the object region Accordingly, a reproduction color that is a color obtained by correcting each pixel in the input image is calculated using a surface reflection component correction unit that corrects the restored surface reflection component, a complete diffusion component, and a corrected surface reflection component.
- reproduction color calculation means for generating an output image based on the reproduction color.
- the color image processing program allows a computer to detect an object area, which is an area to be subjected to image processing, from an input image, color information in the object area, and low frequency in the object area.
- a reflection component restoration process that calculates a perfect diffusion component that is a component and restores a surface reflection component based on the color information and low frequency component, and a reference surface reflection component that is a surface reflection component that is preset according to the object area
- a reproduction color that is a color obtained by correcting each pixel in the input image by using a surface reflection component correction process for correcting the restored surface reflection component and a completely diffused component and a corrected surface reflection component.
- a reproduction color calculation process for generating an output image based on the reproduction color is executed.
- FIG. 1 is a block diagram showing an embodiment of a color image processing apparatus according to the present invention. It is a flowchart which shows the example of the color image processing method in the 1st Embodiment of this invention. It is explanatory drawing which shows the example of the process which detects the target object area
- the color image processing apparatus when improving the texture of the specific object in the input image, the color image processing apparatus first calculates the low-frequency component of the specific object in the input image. Next, the color image processing apparatus uses the calculated low-frequency component as a complete diffusion component including shadow information on the specific object. Then, the color image processing device calculates a surface reflection component (highlight) on the specific object by subtracting a complete diffusion component (including shadow information) from the input image.
- the color image processing apparatus corrects the calculated amount of the surface reflection component of the specific object to a desired amount. Then, the color image processing apparatus calculates the reproduction color of the specific object using the corrected surface reflection component and the complete diffusion including the shadow information.
- the reproduction color is a color obtained by correcting each pixel in the input image, and is calculated from the corrected surface reflection component and complete diffusion component. In this way, the apparent texture after the correction of the specific object can be expressed with a more natural and more desirable texture.
- FIG. 1 is an explanatory diagram showing an example of color image processing in the present invention. The outline of the color image processing method performed by the color image processing apparatus according to the present invention will be further described below with reference to FIG.
- the color image processing apparatus acquires information about an input image to be input (hereinafter referred to as image information acquisition processing). Specifically, when an input image is input, the color image processing apparatus specifies a specific object from the input image. The specific object is an area specified as an object to be corrected. The color image processing apparatus detects a region for correcting the surface reflection component (hereinafter also referred to as a target region) by specifying a specific target. In addition, the color image processing apparatus acquires color information of the specific object (that is, the color of the object area).
- image information acquisition processing Specifically, when an input image is input, the color image processing apparatus specifies a specific object from the input image. The specific object is an area specified as an object to be corrected. The color image processing apparatus detects a region for correcting the surface reflection component (hereinafter also referred to as a target region) by specifying a specific target. In addition, the color image processing apparatus acquires color information of the specific object (that is, the color of the object area).
- the color image processing apparatus restores the reflection information of the specific object (hereinafter referred to as reflection information restoration process).
- the reflection information is information regarding reflected light reflected on the specific object.
- the reflection information of the specific object is generally restored based on the illumination geometric condition based on the three-dimensional shape of the specific object.
- the low-frequency component of the specific object is used instead of the three-dimensional shape.
- the color image processing apparatus sets a low-frequency component of a specific object as a complete diffusion component including shadow information.
- the color image processing apparatus restores the surface reflection component by removing the low frequency component from the color information of the specific object.
- the color image processing device calculates the surface reflection component by subtracting the low frequency component from the color information for the pixel value of each pixel of the input image.
- the color information of the specific object is separated into the surface reflection component and the complete diffusion component (that is, the complete diffusion component including the shadow information). That is, the surface reflection component is restored.
- the surface reflection component is a component of reflected light reflected on the surface of the object, and is information indicating so-called “shine”.
- the complete diffusion component is a low-frequency component of the specific object, and the shadow information is information indicating the luminance of the complete diffusion component.
- the color image processing apparatus corrects the surface reflection component (hereinafter referred to as surface reflection component correction processing). Specifically, the color image processing apparatus corrects the surface reflection component using the average value of the surface reflection component and the reference surface reflection component.
- the reference surface reflection component is a surface reflection component set in advance according to a specific object (object area), which is determined to be a preferable texture by a user or the like.
- the color image processing apparatus calculates a reproduction color of a specific object using a complete diffusion component including shadow information and a corrected surface reflection component (hereinafter, sometimes referred to as a corrected surface reflection component) (hereinafter, referred to as a corrected surface reflection component). This is referred to as a reproduction color calculation process).
- a corrected surface reflection component hereinafter, sometimes referred to as a corrected surface reflection component
- the object area detected from the specific object is composed of a plurality of pixels.
- Each pixel has color information.
- the color information may be referred to as a pixel value.
- the color information includes at least a surface reflection component and a complete diffusion component (including shadow information).
- the color information may include information regarding colors other than those described above.
- it demonstrates without distinguishing a specific target object and a target object area
- FIG. 2 is a block diagram showing an embodiment of a color image processing apparatus according to the present invention.
- the color image processing apparatus 100 illustrated in FIG. 2 includes an image information acquisition unit 110, a reflection information restoration unit 120, a surface reflection component correction unit 130, and a reproduction color calculation unit 140.
- the image information acquisition unit 110 specifies a specific object based on an input image input from the outside, and detects an object area of the specific object. Further, the image information acquisition unit 110 acquires color information of the object area.
- the reflection information restoration unit 120 calculates a low frequency component of the object area.
- the calculated low frequency component is a complete diffusion component including shadow information in the object region.
- the reflection information restoring unit 120 restores the surface reflection component in the object area by removing the complete diffusion component from the color information of the object area. That is, the color information in the object region is separated into a surface reflection component (shine) and a complete diffusion component, and is restored as each component.
- the surface reflection component correction unit 130 corrects the surface reflection component restored by the reflection information restoration unit 120.
- correcting the surface reflection component means changing the area of the pixel having the surface reflection component or changing the intensity of the surface reflection component.
- the surface reflection component correction unit 130 may correct the surface reflection component by changing the shape of the surface reflection component.
- the surface reflection component correction unit 130 may correct the expression reflection component by increasing or decreasing the intensity of the surface reflection component.
- the surface reflection component correction unit 130 calculates the average value of the surface reflection components of the object region, and corrects the surface reflection component using the calculated average value.
- the surface reflection component correction unit 130 may correct the surface reflection component by comparing an arbitrary value set in advance with an average value of the surface reflection components of the object region.
- the surface reflection component correction unit 130 may use, for example, a reference surface reflection component as an arbitrary value.
- the reference surface reflection component is stored in advance, for example, in a memory (hereinafter referred to as a reference surface reflection component storage memory) provided in the color image processing apparatus 100.
- the surface reflection component correction unit 130 may receive a correction value from the user and correct the surface reflection component using the received correction value.
- the correction value is a generic name of information used when the surface reflection component correction unit 130 corrects the surface reflection component.
- correcting the amount of the surface reflection component means correcting the area of the pixel of the surface reflection component or correcting the pixel value indicating the intensity of the surface reflection component.
- the reproduction color calculation unit 140 calculates a reproduction color using the complete diffusion component including the shadow information and the corrected surface reflection component. Then, the reproduction color calculation unit 140 generates an output image using the calculated reproduction color.
- the image information acquisition unit 110 acquires a low-frequency component in the object region.
- the reflection information restoration unit 120 restores the surface reflection component and the complete diffusion component in the region using the acquired low frequency component in the object region.
- the surface reflection component correction unit 130 corrects the restored surface reflection component.
- the color image processing apparatus 100 can correct the surface reflection component restored by using the low frequency component in the object region.
- the reflection information restoration unit 120 restores the surface reflection component of the object region and the complete diffusion component including the shadow information from the color information obtained from the image, and the surface reflection component correction unit 130 performs only the surface reflection component. Make corrections. By performing these processes, the occurrence of unnatural artifacts is suppressed. Furthermore, the processing cost can be kept low by not restoring the three-dimensional information.
- FIG. 3 is a flowchart showing an example of a color image processing method according to the first embodiment of the present invention.
- the color image processing method in the present embodiment is realized using the color image processing apparatus 100 illustrated in FIG.
- the color system of the image is the RGB color system. That is, the color of the image is represented by a combination of R (red), G (green), and B (blue).
- the color information of the input image is expressed as color information RGB.
- the color system of the image is not limited to the RGB color system.
- the color system of the image may be a color system other than RGB.
- the color image processing apparatus 100 illustrated in FIG. 2 recalculates the reproduction color at each pixel of the object region in the color image in order to improve the texture of the specific object in the given color image. The operation of performing will be described.
- the image information acquisition unit 110 automatically detects a specific object from the input image (step S1). At this time, the image information acquisition unit 110 also acquires the color information of the object area in the detected specific object.
- a specific object from an input image means that a predetermined object (for example, a human face) is detected from the input image as a specific object, or is specified individually by a user or the like. This means that the object is detected as a specific object.
- the individual as the specific object may be different. That is, even if there are individual differences, rough color information and texture are universal, so if the target object can be identified from the characteristics obtained from the color image, It is not limited to individuals.
- FIG. 4 is an explanatory diagram showing an example of processing for detecting an object region in an input image.
- a human face is used as the object area.
- the image information acquisition unit 110 detects the specific object from the color image illustrated in FIG. 4 using color information, texture, and the like.
- the specific object is a human face will be described.
- the image information acquisition unit 110 detects a face area using shape features such as eyes, nose, and mouth.
- the image information acquisition unit 110 may use, for example, the face detection method described in Non-Patent Document 2 as a method for detecting the face area.
- the face detection method described in Non-Patent Document 2 is a method using generalized learning vector quantization that combines an image-based type and a feature-based type for eye detection.
- the image information acquisition unit 110 may use, for example, a method for detecting eyes from an image described in Patent Document 2 as a method for detecting a face region from an input image. If the eye position can be detected from the input image, it is easy to estimate the face area.
- the face detection method described in Non-Patent Document 2 and the eye detection method described in Patent Document 2 usually perform face detection using monochrome information.
- the image information acquisition unit 110 may further determine whether or not the face area that is the detection result is a skin color. By adding such a determination process, the detection accuracy of the face region can be improved.
- an image histogram described in Patent Document 1 may be used as a method for determining whether or not the designated region is flesh-colored.
- the method by which the image information acquisition unit 110 detects the face area from the input image is not limited to the above method.
- an object to be automatically detected from an arbitrarily given input image is a human face.
- the object to be automatically detected is not limited to a human face.
- the image information acquisition unit 110 compares, for example, visual feature information of a target area registered in advance with visual feature information of image data. The object may be automatically detected.
- the reflection information restoration unit 120 calculates a surface reflection component and a complete diffusion component.
- the surface reflection component (shine) of the specific object in the image has a high frequency component.
- the reflection information restoration unit 120 uses the apparent color information of the specific object without using the three-dimensional shape of the specific object, and the surface reflection component (shine) and the complete diffusion component (including shadow information). Is calculated. Therefore, the surface reflection component can be calculated at a low calculation cost.
- these processes performed by the reflection information restoration unit 120 will be described in detail in steps S2 to S3.
- the reflection information restoration unit 120 calculates the low frequency component of the region indicated by the specific object in the image (step S2). For example, the reflection information restoration unit 120 may calculate a low frequency component by calculating an average value of surrounding pixels for each pixel in a region indicated by a specific object in the image. Further, the reflection information restoration unit 120 may calculate the low frequency component by using a smoothing filter that replaces each pixel with a value such as Gaussian.
- the method for calculating the low frequency component is not limited to the above method.
- the reflection information restoration unit 120 sets the low frequency component calculated in step S2 as a complete diffusion component in the specific object in the input image. Then, the reflection information restoration unit 120 calculates a surface reflection component by subtracting the complete diffusion component from the color information of the specific object in the input image (step S3).
- the reflectance of the object region depends on the geometric conditions of incident light and radiated light, and this reflection characteristic is expressed as a bidirectional reflectance distribution function BRDF (Bidirectional Reflection Distribution Function).
- the BRDF is often composed of two components, a surface reflection component (Sectional component) and a complete diffusion component (Body reflection component).
- the surface reflection component is a component of light reflected on the surface of the skin.
- the completely diffusing component is a component of light once incident on the inside of the skin and light diffused in the inside once again diverges through the skin.
- the fully diffusing component has a low frequency characteristic. Therefore, the low frequency component in the region indicated by the specific object can be regarded as a complete diffusion component DR (Diffuse Reflection) of the specific object.
- the perfect diffusion component DR is calculated for each color channel (for example, R, G, B, etc.), and the perfect diffusion component of each color channel is expressed as DRi. Note that i represents each color channel.
- the perfect diffusion component is calculated assuming that the specific object is a Lambertian.
- the complete diffuse component includes not only the diffuse reflection component but also the surface reflection component. That is, it can be said that the pixel value of each color channel of the input image represents the apparent pixel value (luminance, brightness) in the color channel including the diffuse reflection component and the surface reflection component. Therefore, the reflection information restoration unit 120 calculates the surface reflection component SPi of each color channel of the pixel included in the region indicated by the specific object using the following Expression 1.
- Ii represents a pixel value of a pixel included in a region indicated by the specific object of the input image
- i represents a color channel (for example, R, G, B, etc.).
- the surface reflection component correction unit 130 corrects the surface reflection component of the specific object (step S4). Specifically, when the surface reflection component in the specific object region in the color image is obtained, the surface reflection component correction unit 130 controls the amount (area or intensity) of the surface reflection component to thereby specify the specific object. Improve the texture.
- controlling the “area” means increasing or decreasing the number (region) of pixels including the surface reflection component.
- controlling “intensity” means increasing or decreasing the value of each pixel of the surface reflection component. That is, the surface reflection component correction unit 130 controls or adjusts the amount of the surface reflection component such as the area of the surface reflection component or the intensity of the specific object in the input color image, thereby adjusting the desired surface reflection component. Is generated.
- the surface reflection component correction unit 130 corrects the intensity of the surface reflection component as the amount of the surface reflection component.
- the amount of the desired surface reflection component that is, the reference surface reflection component
- the average amount of the surface reflection component is expressed as follows.
- This average can be calculated as follows. First, an image (hereinafter referred to as a reference image) in which the texture of the specific object is good by a user or the like is prepared in advance. Then, the surface reflection component of the specific object is calculated by performing the processing shown in steps S1 to S3 described above on the reference image. In addition, it can be said that this reference image is an image in which a surface reflection component that is determined to have a good texture by a user or the like is set in advance according to the object region.
- the surface reflection component in each pixel calculated from the reference image is denoted as SPRi. Since this SPRi indicates a pixel value in each pixel, the surface reflection component correction unit 130 can calculate the average of the amount of the surface reflection component by calculating the average of this SPRi.
- the surface reflection component correction unit 130 calculates the average value of the surface reflection components in the object region in the input image.
- the average value of the surface reflection components in the object area in the input image is expressed as follows.
- the surface reflection component correction unit 130 calculates a correction coefficient ⁇ i according to the following equation 2 based on each average value.
- the surface reflection component correction unit 130 After calculating the correction coefficient, the surface reflection component correction unit 130 multiplies ⁇ i calculated by Equation 2 by the surface reflection component SPi in the object region in the input image, thereby obtaining a desired amount (intensity) of the surface reflection component. To correct.
- the surface reflection component correction unit 130 may correct the amount of the surface reflection component using, for example, the following Expression 3.
- the surface reflection component correction unit 130 includes the average value of the surface reflection components in the object region of the input image and the surface reflection component (that is, the reference surface reflection component) set in advance according to the object region.
- the pixel value of the surface reflection component is corrected according to the ratio with the average value.
- the texture can be improved by correcting the intensity of the surface reflection component of the object region.
- the surface reflection component correction unit 130 corrects the area of the surface reflection component as the amount of the surface reflection component. Even when the area of the surface reflection component is corrected, the surface reflection component of the object region in the preset reference image is used as in the case of correcting the intensity. However, when correcting the area, the amount (area) of the surface reflection component in the specific object of the input image is adjusted using the desired amount (area) of the surface reflection component.
- the area may be expressed as a ratio of the number of pixels of the surface reflection component to the number of pixels of the object region.
- the surface reflection component correction unit 130 causes the number of pixels (that is, the area) of the surface reflection component in the area of the specific object in the input image to approach the amount (area) of the desired surface reflection component in the object area. Correct the surface reflection component. Specifically, the surface reflection component correction unit 130 uses a coefficient ⁇ i ( ⁇ i ⁇ i) that decreases the amount (intensity) of the surface reflection component in Equation 3 instead of ⁇ i described above, and uses the coefficient ⁇ i ( ⁇ i ⁇ i) in Equation 3. Correction is performed to reduce the amount (intensity).
- the surface reflection component correction unit 130 sets the pixel value SPi ′ of the pixel whose corrected pixel value SPi ′ is below a predetermined threshold to 0 (zero). Thus, by setting the surface reflection component to 0, the amount (area) of the surface reflection component is reduced.
- the surface reflection component correction unit 130 determines the area of the surface reflection component in the object region of the input image as the area of the surface reflection component (that is, the reference surface reflection component) set in advance according to the object region. Make corrections to decrease. At this time, the surface reflection component correction unit 130 reduces the pixel value of the surface reflection component in the object region based on a predetermined rule, such as multiplying the pixel value by a coefficient that decreases the pixel value of the surface reflection component. And the surface reflection component correction
- Equation 1 a pixel that was not originally a surface reflection component does not become a surface reflection component as it is. Therefore, in order to increase the area of the surface reflection component, it is necessary to perform a separate process.
- the surface reflection component correction unit 130 is, for example, a pixel that was not originally a surface reflection component (that is, a pixel that the reflection information restoration unit 120 did not restore as a surface reflection component) and originally a surface reflection component.
- a pixel adjacent to the selected pixel that is, a pixel restored by the reflection information restoration unit 120 as a surface reflection component
- the front reflection component correction unit 130 calculates the corrected pixel value SPi ′ by substituting the pixel value of the selected pixel into SPi in Expression 3, for example.
- the surface reflection component correction unit 130 adds a positive real number to the pixel value (that is, the surface reflection component) SPi of the selected pixel.
- the surface reflection component correction unit 130 may calculate the corrected pixel value SPi ′ using a coefficient that increases the pixel value so that the area increases, instead of the coefficient ⁇ i. Thereafter, the surface reflection component correction unit 130 randomly selects a pixel adjacent to the pixel that was originally the surface reflection component until a desired area is reached, and repeats the operation of correcting the pixel value of the pixel. Thus, by increasing the pixels of the surface reflection component, the amount (area) of the surface reflection component is increased.
- the surface reflection component correction unit 130 determines the area of the surface reflection component in the object region of the input image as the area of the surface reflection component (that is, the reference surface reflection component) set in advance according to the object region. The correction to increase is performed. In that case, the surface reflection component correction
- the reproduction color calculation unit 140 uses the corrected surface reflection component and the complete diffusion component (including shadow information) to calculate the corrected color of each pixel in the target object in the input image (step). S5). Note that this corrected color can be referred to as a reproduced color.
- the reproduction color calculation unit 140 adds the surface reflection component Spi ′ corrected in step S4 to the complete diffusion component DRi including the shadow information, as illustrated in Equation 4 below, so that the pixel value after color correction Ii ′ is calculated.
- the reproduction color calculation unit 140 outputs an image obtained by correcting the color of the object area in the input image according to the above method as an output image.
- the device-dependent color of the input image and the output image is RGB.
- the device-dependent color means a color space that depends on the output destination device.
- this device-dependent color is not limited to RGB. If the correspondence between the device-dependent color and the tristimulus values XYZ of the device-independent color is obtained, the device-dependent color may be CMY or CMYK other than RGB. In this case, the color correction method of the present invention can be applied to images other than RGB.
- the image information acquisition unit 110 detects the object region from the input image.
- the reflection information restoration unit 120 calculates the color information and the complete diffusion component in the object region, and restores the surface reflection component based on the color information and the low frequency component.
- the reproduction color calculation unit 140 uses the complete diffusion component and the corrected surface reflection component to reproduce the color. And an output image is generated based on the reproduced color. Therefore, the texture of the object in the color image can be improved at a low calculation cost.
- FIG. 5 is a block diagram illustrating an example of a color image processing apparatus applied to the color image processing method according to the first embodiment.
- the color image processing apparatus 101 illustrated in FIG. 5 is an apparatus that outputs the output image 2 by correcting the surface reflection component of the object region in the input image 1.
- the color image processing apparatus 101 includes an object area detection unit 3, an object area low frequency component calculation unit 4 (hereinafter, low frequency component calculation unit 4), an object area surface reflection component, and a complete diffusion component calculation unit. 5 (hereinafter referred to as a reflection information restoration unit 5), a surface reflection component correction unit 6, a reference surface reflection component storage memory 7, and a reproduction color calculation unit 8 for an object region (hereinafter referred to as a reproduction color calculation unit 8). ing.
- the object area detection unit 3 analyzes the input image 1 and detects a specific object assumed in advance. Then, the object area detection unit 3 outputs information indicating the object area in the detected specific object.
- the information indicating the object area includes color information of the object area.
- the target area detection unit 3 obtains the color information of the target area using the method performed by the image information acquisition unit 110 described in step S1 of FIG.
- the specific object detected from the input image 1 can limit the color and shape characteristics of the object area to some extent, such as a human face. Note that the method for detecting the specific object is as described in the description of the image information acquisition unit 110. If the target object cannot be detected from the input image 1, the reproduction color calculation unit 12 described later outputs the input image 1 as the output image 2.
- the low frequency component calculation unit 4 calculates the low frequency component of the object area detected by the object area detection unit 3. Specifically, the low frequency component calculation unit 6 calculates the low frequency component of the object region based on the process performed by the reflection information restoration unit 120 described in step S2.
- the reflection information restoration unit 5 obtains a surface reflection component and a complete diffusion component in the object region using the low frequency component of the object region. Specifically, the reflection information restoration unit 5 obtains a surface reflection component and a complete diffusion component in the object region according to the process performed by the reflection information restoration unit 120 described in step S3.
- the reference surface reflection component storage memory 7 stores the reference surface reflection component of the object area.
- the reference surface reflection component is a surface reflection component that provides a preferable image quality of the object region, and is set in the reference surface reflection component storage memory 7 in advance according to the object region.
- the surface reflection component correction unit 6 corrects the amount of the surface reflection component to a desired amount using the reference surface reflection component for the calculated surface reflection component in the object region. Specifically, the surface reflection component correction unit 6 corrects the surface reflection component in the object region according to the process performed by the surface reflection component correction unit 130 described in step S4 of FIG.
- the surface reflection component correction unit 6 performs the above correction, the color of an object having complicated reflection characteristics, such as human skin, can be accurately reproduced. Further, by performing the above correction, it is possible to avoid the occurrence of artifacts.
- the reproduction color calculation unit 8 calculates the reproduction color of the object area. Specifically, the reproduction color calculation unit 8 uses the corrected surface reflection component and the complete diffusion component including the shadow information to calculate the corrected color (that is, the reproduction color) of each pixel in the object region. calculate. Then, the reproduction color calculation unit 12 outputs the calculated corrected image as an output image.
- the corrected surface reflection component is a component corrected by the surface reflection component correction unit 6 and indicates a preferable surface reflection component of each pixel in the object region.
- the complete diffusion component is a component calculated by the reflection information restoration unit 5.
- the reproduction color calculation unit 12 outputs the corrected image according to the processing procedure performed by the reproduction color calculation unit 150 described in step S5.
- the color image processing apparatus 101 provides a method of improving the image quality by adjusting the surface reflection component, that is, the shine, as a method of realizing a desirable image quality of the human face.
- Such shine is also an unpleasant specular component.
- Patent Document 7 described above describes, as a related technique, a method for changing the color of an artificial object such as a plastic having a dichroic reflection model from red to blue.
- the method described in Patent Document 7 is intended to change the color of an artifact to another color (change the color), and does not improve the image quality and correct it to a desired image quality.
- the surface reflection component correction unit 6 corrects the surface reflection component
- the reproduction color calculation unit 8 generates an output image using the corrected surface reflection component. That is, since the color image processing apparatus 101 includes the surface reflection component correction unit 6 and the reproduction color calculation unit 8, the object can be corrected to a desired image quality.
- the image information acquisition unit 110 corresponds to the object area detection unit 3.
- the reflection information restoration unit 120 is realized by the low frequency component calculation unit 4 and the reflection information restoration unit 5.
- the surface reflection component correction unit 130 is realized by the surface reflection component correction unit 6 and the reference surface reflection component storage memory 7.
- the reproduction color calculation unit 140 corresponds to the reproduction color calculation unit 8.
- the configuration of the color image processing apparatus shown in FIG. 2 or FIG. 5 is an example, and other configurations may be used as long as the apparatus can realize the same function.
- the color image processing apparatus 101 can be realized by a computer. Specifically, each component constituting the color image processing apparatus, that is, the object region detection unit 3, the low frequency component calculation unit 4, the reflection information restoration unit 5, the surface reflection component correction unit 6, and the reproduction
- the color calculation unit 8 is realized by a central processing unit (CPU) of a computer that operates according to a program (color image processing program).
- the representative surface reflection component storage memory 7 is realized by a memory device included in the color image processing apparatus 101, for example.
- the program is stored in a storage unit (not shown) of the color image processing apparatus 101, and the CPU reads the program, and in accordance with the program, the object region detection unit 3, the low frequency component calculation unit 4, the reflection information restoration The unit 5, the surface reflection component correction unit 6, and the reproduction color calculation unit 8 may be operated. Further, the object area detection unit 3, the low frequency component calculation unit 4, the reflection information restoration unit 5, the surface reflection component correction unit 6, and the reproduction color calculation unit 8 are each realized by dedicated hardware. It may be.
- each component constituting the color image processing apparatus can be realized by a CPU and a memory, and can be operated according to a program, not only in the first embodiment but also in a second embodiment described later. is there.
- Embodiment 2 a color image processing method according to the second embodiment of the present invention will be described.
- the color image processing method in the second embodiment is different from the color image processing method in the first embodiment in that the surface reflection component is changed in accordance with a user instruction.
- FIG. 6 is a block diagram illustrating an example of a color image processing apparatus applied to the color image processing method according to the second embodiment.
- a color image processing apparatus 102 illustrated in FIG. 6 is an apparatus that outputs the output image 2 by correcting the surface reflection component of the object region in the input image 1.
- the color image processing apparatus 102 includes an object region detection unit 3, a low frequency component calculation unit 4, a reflection information restoration unit 5, a surface reflection component correction unit 6, a user interaction unit 9, and a reproduction color calculation unit 8. It has.
- the color image processing apparatus 102 is obtained by replacing the reference surface reflection component storage memory 7 of the color image processing apparatus 101 illustrated in FIG. Therefore, only the user interaction unit 9 will be described below.
- the user interaction unit 9 provides an interaction means for the user to adjust the amount of the surface reflection component in the region of the specific object in the input image.
- the user interaction unit 9 is an input unit that inputs the amount of the surface reflection component in the region of the specific object in the input image.
- the user interaction unit 9 is realized by, for example, a touch panel, a display device such as a display, and a pointing device such as a mouse.
- FIG. 7 is an explanatory diagram showing an example of a graphical user interface (GUI) displayed by the user interaction unit 9.
- GUI graphical user interface
- the GUI illustrated in FIG. 7 interactively adjusts the amount of the surface reflection component in the specific object region in the calculated input image.
- the slider bar 10 illustrated in FIG. 7 has a function of adjusting the value of ⁇ i in the above formula (3), for example.
- the user interaction unit 9 may adjust the value of ⁇ i to be small (see FIG. 7A).
- the user interaction unit 9 may adjust the value of ⁇ i so as to increase (see FIG. 7B).
- the user interaction unit 9 displays a correction image that reflects the adjustment result of the surface reflection component in the input image in real time.
- the user interaction unit 9 receives the amount (correction value) of the surface reflection component input from the user, and notifies the surface reflection component correction unit 6 of it.
- the correction value may be a value that specifies the total amount of the surface reflection component, or may be a value that indicates the amount to be changed from the current surface reflection component.
- the surface reflection component correction unit 6 corrects the surface reflection component of each pixel using the notified amount of the surface reflection component. In this way, an output image desired by the user can be generated.
- the surface reflection component correction unit 6 corrects the surface reflection component using the method of reducing the area of the surface reflection component or the method of reducing the area of the surface reflection component described in the first embodiment. That's fine.
- the surface reflection component correction unit 6 corrects the intensity of the surface reflection component described in the first embodiment.
- the surface reflection component may be corrected using
- the color image processing apparatus 102 is not limited to the case where it includes any one component of the reference surface reflection component storage memory 7 and the user interaction unit 9.
- the color image processing apparatus 102 may include components of both the reference surface reflection component storage memory 7 and the user interaction unit 9.
- the surface reflection component correction unit 6 corrects the surface reflection component using the reference surface reflection component stored in the reference surface reflection component storage memory 7. Then, the user interaction unit 9 displays an image including the corrected surface reflection component to the user. The user can input a correction value via the user interaction unit 9 when the user desires to change the surface reflection component of the corrected image. Thereby, the surface reflection component correction
- the color image processing method and apparatus according to the present invention can be realized using a computer.
- Each process performed by the color image processing method and the color image processing apparatus according to the present invention can also be realized by a combination of two or more of software, hardware, and firmware.
- the program causes the computer to execute at least the following procedure.
- the program is loaded into the memory of the computer, and the following instructions (a) to (d) are executed under the control of the CPU.
- (C) A surface reflection component correction procedure for correcting the restored surface reflection component according to a reference surface reflection component which is a surface reflection component set in advance according to the object region. This procedure corresponds to the processing performed by the surface reflection component correction unit 130 in FIG.
- the command executed by the program may include a user interaction procedure in which a correction value, which is information used when correcting the surface reflection component, is input from the user.
- a correction value which is information used when correcting the surface reflection component
- the program can be provided by being recorded on a recording medium, or can be provided by being transmitted through the Internet or other communication media.
- the storage medium includes, for example, a flexible disk, a hard disk, a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD, a ROM cartridge, a battery-backed RAM memory cartridge, a flash memory cartridge, and a nonvolatile RAM cartridge.
- the communication medium includes a wired communication medium such as a telephone line, a wireless communication medium such as a microwave line, and the like.
- the texture can be improved by controlling the amount of the surface reflection component in the specific object in the color image taken by the color image device.
- the present invention solves the problem of deterioration of the texture of an object that occurs when a general color correction method is used.
- the object region can be changed to have a desired texture by controlling the surface reflection component of the specific object in the color image taken by the color image device.
- FIG. 8 is a block diagram showing an example of the minimum configuration of the color image processing apparatus according to the present invention.
- the color image processing apparatus according to the present invention includes a target area detection unit 81 (for example, an image information acquisition unit 110) that detects a target area that is a target area for image processing from an input image, and color information in the target area. And a reflection component restoration that calculates a perfect diffusion component that is a low frequency component in the object region and restores a surface reflection component based on the color information and the low frequency component (for example, by removing the low frequency component from the color information).
- a target area detection unit 81 for example, an image information acquisition unit 110
- a reflection component restoration that calculates a perfect diffusion component that is a low frequency component in the object region and restores a surface reflection component based on the color information and the low frequency component (for example, by removing the low frequency component from the color information).
- Means 82 for example, reflection information restoration unit 120
- surface reflection component correction means for correcting the restored surface reflection component according to the reference surface reflection component which is a surface reflection component preset according to the object region 83 (for example, the surface reflection component correction unit 130), the complete diffusion component, and the corrected surface reflection component are used to calculate a reproduction color that is a color obtained by correcting each pixel in the input image.
- a reproduced color calculation means 84 for generating an output image based on the reproduced color (e.g., reproduced color calculation unit 140).
- the color image processing apparatus has a correction value input unit (for example, a user interaction unit 9) that inputs a correction value (for example, the amount of the surface reflection component) that is information used when correcting the surface reflection component. May be provided.
- the surface reflection component correction unit 83 may correct the surface reflection component using the input correction value.
- the surface reflection component correction unit 83 determines whether the average value of the surface reflection component in the object region of the input image and the average value of the reference surface reflection component (for example, a coefficient calculated by Equation 2) The pixel value of the surface reflection component may be corrected (for example, corrected using Equation 3).
- the surface reflection component correcting unit 83 corrects the area of the surface reflection component so as to approach the area of the reference surface reflection component in the object region or the ratio of the area of the reference surface reflection component in the object region. Good.
- the surface reflection component correcting unit 83 multiplies the pixel value by a predetermined rule (for example, a coefficient ⁇ i that decreases the amount (intensity) of the surface reflection component) of the pixel value of the surface reflection component in the object region. And reducing the area of the surface reflection component by excluding from the surface reflection component pixels whose pixel values are less than a predetermined threshold among the pixel values.
- a predetermined rule for example, a coefficient ⁇ i that decreases the amount (intensity) of the surface reflection component
- the surface reflection component correcting unit 83 selects a pixel adjacent to the surface reflection component among the pixels that are not the surface reflection component based on a predetermined rule (for example, a rule for selecting at random), and selects the selected pixel. Correction for increasing the area of the surface reflection component may be performed by adding the surface reflection component.
- the present invention can be suitably applied to a function for improving the image quality of an image input to a color image input / output device.
- the present invention can be applied as image correction software or utility for an arbitrary color image by adopting a program that operates in a computer system.
Abstract
Description
まず、本発明の第1の実施形態におけるカラー画像処理方法を、図面を用いて処理の流れを説明する。図3は、本発明の第1の実施形態におけるカラー画像処理方法の例を示すフローチャートである。なお、以下の説明では、本実施形態におけるカラー画像処理方法を、図2に例示するカラー画像処理装置100を用いて実現するものとする。また、以下の説明では、画像の表色系がRGB表色系であるものとする。すなわち、画像の色が、R(赤)、G(緑)およびB(青)の組み合わせで表されるものとする。以下、入力画像の色情報のことを、色情報RGBと表記するものとする。ただし、画像の表色系は、RGB表色系に限定されない。画像の表色系は、RGB以外の他の表色系であってもよい。
上記以外 SPi=0 (式1)
次に、本発明の第2の実施形態におけるカラー画像処理方法について説明する。第2の実施形態におけるカラー画像処理方法は、ユーザの指示に応じて表面反射成分を変更する点において、第1の実施形態におけるカラー画像処理方法と異なる。
2 出力画像
3 対象物領域検出部
4 対象物領域の低周波成分計算部
5 対象物領域の表面反射成分と完全拡散成分計算部
6 表面反射成分補正部
7 参照表面反射成分保存メモリ
8 対象物領域の再現色算出部
9 ユーザ対話部
10 スライダーバー
100,101,102 カラー画像処理装置
110 画像情報取得部
120 反射情報復元部
130 表面反射成分補正部
140 再現色算出部
Claims (10)
- 画像処理の対象とする領域である対象物領域を入力画像から検出し、
前記対象物領域における色情報及び当該対象物領域における低周波成分である完全拡散成分を算出し、
前記色情報及び低周波成分に基づいて表面反射成分を復元し、
対象物領域に応じて予め設定された表面反射成分である参照表面反射成分に応じて、復元された表面反射成分を補正し、
前記完全拡散成分と、補正された表面反射成分とを用いて、入力画像における各画素を補正した色である再現色を算出し、
前記再現色に基づいて出力画像を生成する
ことを特徴とするカラー画像処理方法。 - 表面反射成分の補正を行う際に用いる情報である補正値をユーザから入力され、
復元された表面反射成分を補正する際、入力された補正値を用いて表面反射成分を補正する
請求項1記載のカラー画像処理方法。 - 復元された表面反射成分を補正する際、入力画像の対象物領域における表面反射成分の平均値と、参照表面反射成分の平均値との比率に応じて、表面反射成分の画素値を補正する
請求項1または請求項2に記載のカラー画像処理方法。 - 復元された表面反射成分を補正する際、対象物領域における参照表面反射成分の面積、または、対象物領域における参照表面反射成分の面積の割合に近づけるように、表面反射成分の面積を補正する
請求項1または請求項2に記載のカラー画像処理方法。 - 復元された表面反射成分を補正する際、対象物領域における表面反射成分の画素値を所定の規則に基づいて減少させ、当該画素値のうち、予め定められた閾値を下回る画素値の画素を表面反射成分から除外することにより、表面反射成分の面積を減少させる補正を行う
請求項4記載のカラー画像処理方法。 - 復元された表面反射成分を補正する際、表面反射成分でない画素のうち、表面反射成分に隣接する画素を所定の規則に基づいて選択し、選択した画素を表面反射成分として追加することにより、表面反射成分の面積を増加させる補正を行う
請求項4記載のカラー画像処理方法。 - 画像処理の対象とする領域である対象物領域を入力画像から検出する対象物領域検出手段と、
前記対象物領域における色情報及び当該対象物領域における低周波成分である完全拡散成分を算出し、当該色情報及び低周波成分に基づいて表面反射成分を復元する反射成分復元手段と、
対象物領域に応じて予め設定された表面反射成分である参照表面反射成分に応じて、復元された表面反射成分を補正する表面反射成分補正手段と、
前記完全拡散成分と、補正された表面反射成分とを用いて、入力画像における各画素を補正した色である再現色を算出し、当該再現色に基づいて出力画像を生成する再現色算出手段とを備えた
ことを特徴とするカラー画像処理装置。 - 表面反射成分の補正を行う際に用いる情報である補正値をユーザから入力される補正値入力手段を備え、
表面反射成分補正手段は、入力された補正値を用いて表面反射成分を補正する
請求項7記載のカラー画像処理装置。 - コンピュータに、
画像処理の対象とする領域である対象物領域を入力画像から検出する対象物領域検出処理、
前記対象物領域における色情報及び当該対象物領域における低周波成分である完全拡散成分を算出し、当該色情報及び低周波成分に基づいて表面反射成分を復元する反射成分復元処理、
対象物領域に応じて予め設定された表面反射成分である参照表面反射成分に応じて、復元された表面反射成分を補正する表面反射成分補正処理、および、
前記完全拡散成分と、補正された表面反射成分とを用いて、入力画像における各画素を補正した色である再現色を算出し、当該再現色に基づいて出力画像を生成する再現色算出処理
を実行させるためのカラー画像処理プログラム。 - コンピュータに、
表面反射成分の補正を行う際に用いる情報である補正値をユーザから入力された場合に、当該補正値を用いて表面反射成分を補正させる
請求項9記載のカラー画像処理プログラム。
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JPWO2012001949A1 (ja) | 2013-08-22 |
EP2590136A1 (en) | 2013-05-08 |
JP5867390B2 (ja) | 2016-02-24 |
CN102985941B (zh) | 2015-08-19 |
US8855371B2 (en) | 2014-10-07 |
US20130083969A1 (en) | 2013-04-04 |
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