CN112927153A - Image processing method and device - Google Patents
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Abstract
The invention provides an image processing method and device. The image processing method comprises the following steps: determining high saturation pixels in a target image, wherein the saturation of the high saturation pixels is greater than a preset saturation threshold, and the brightness values of the high saturation pixels are greater than a brightness threshold; determining high-brightness pixels located in a neighborhood of the high-saturation pixel and characteristic values of the high-brightness pixels, wherein the saturation of the high-brightness pixels is less than or equal to the saturation threshold, and the brightness value of the high-brightness pixels is greater than the brightness threshold; and marking the pixel of which the difference value between the characteristic value and the characteristic value of the high-brightness pixel is smaller than a preset characteristic value difference threshold as a target pixel of which the brightness is to be reduced. The embodiment of the invention reduces the possibility of color distortion, reduces the brightness loss and is beneficial to improving the display effect.
Description
Technical Field
The present invention relates to the field of display technologies, and in particular, to an image processing method and apparatus.
Background
The RGBW (red, green, blue and white) display technology is an image display mode in which each pixel includes a red, green, blue and white sub-pixel, and the W sub-pixel has a higher light transmittance, which is helpful to improve the display brightness and save the power consumption. In the related art, an image in RGB (red, green and blue) format is usually converted into a signal matched with an RGBW display device through a specific mapping algorithm, wherein the related mapping algorithm mainly aims to increase the pixel value of the W sub-pixel. In some cases, if the pixel value of the W sub-pixel is too high, the visual effect of the sub-pixels of other colors is diluted, which affects the display effect.
Disclosure of Invention
The embodiment of the invention provides an image processing method and device, and aims to solve the problem that the display effect is influenced by overhigh pixel value of a W sub-pixel.
In a first aspect, an embodiment of the present invention provides an image processing method applied to an image in a red, green, blue, and RGB format displayed on a red, green, blue, and white RGBW display device, where the method includes the following steps:
determining high saturation pixels in a target image, wherein the saturation of the high saturation pixels is greater than a preset saturation threshold, and the brightness values of the high saturation pixels are greater than a brightness threshold;
determining high-brightness pixels located in a neighborhood of the high-saturation pixel and characteristic values of the high-brightness pixels, wherein the saturation of the high-brightness pixels is less than or equal to the saturation threshold, and the brightness value of the high-brightness pixels is greater than the brightness threshold;
and marking the pixel of which the difference value between the characteristic value and the characteristic value of the high-brightness pixel is smaller than a preset characteristic value difference threshold as a target pixel of which the brightness is to be reduced.
Optionally, before determining the high saturation pixel in the target image, the method further includes:
converting the to-be-processed image in the RGB format into a Lab format;
calculating the characteristic value of each pixel in the image to be processed, wherein the characteristic value of each pixel is the arithmetic square root of the sum of squares of the L value, the a value and the b value of the equal-interval quantization value respectively;
and obtaining a target image of at least one object included in the image to be processed according to the characteristic value segmentation of the pixels, wherein the difference value of the characteristic value of each pixel in each target image is smaller than a preset characteristic value difference value threshold.
Optionally, after determining the high saturation pixel in the target image, the method further includes:
executing the step of determining high-brightness pixels located in the neighborhood of the high-saturation pixels and the characteristic values of the high-brightness pixels when the number of the high-saturation pixels is greater than a preset number threshold;
and ending the process under the condition that the number of the high saturation pixels is not more than a preset number threshold.
Optionally, the determining high-brightness pixels located in a neighborhood of the high-saturation pixel and the feature values of the high-brightness pixels includes:
establishing a first binary image of the target image, wherein in the first binary image, the brightness of a high-saturation pixel is a first brightness value, the brightness of a non-high-saturation pixel is a second brightness value, the non-high-saturation pixel is a pixel except the high-saturation pixel, and the first brightness value and the second brightness value are not equal;
performing kernel expansion based on the high saturation pixels in the first binary image, and removing isolated pixel regions with the size smaller than a preset size threshold value in the first binary image;
and taking the pixels with the brightness values larger than the brightness threshold value in the neighborhood of the pixels with the brightness values larger than the first brightness value in the first binary image as high-brightness pixels, and calculating the characteristic value of each high-brightness pixel, wherein one of the pixels is kept as the high-brightness pixel under the condition that the neighborhood of one high-saturation pixel has the same characteristic value and the number of the pixels with the brightness values larger than the brightness threshold value is multiple.
Optionally, after the pixel of which the difference between the characteristic value and the characteristic value of the high-brightness pixel is smaller than the preset characteristic value difference threshold is marked as a target pixel of which the brightness is to be reduced, the method includes:
establishing a second binary image of the target image, wherein in the second binary image, the brightness of a target pixel is a third brightness value, the brightness of a non-target pixel is a fourth brightness value, and the non-target pixel is a pixel except the target pixel;
performing transition processing on a transition region where the target pixel and the non-target pixel are adjacent to each other, so that the brightness value of the pixel in the transition region is between the third brightness value and the fourth brightness value;
determining a degree of luminance reduction of the pixels in the transition region according to the luminance values of the pixels in the transition region, wherein the degree of luminance reduction of the pixels in the transition region increases as a difference between the luminance values and the third luminance value increases.
In a second aspect, an embodiment of the present invention provides an image processing apparatus applied to an image in a red, green, blue, and RGB format displayed on a red, green, blue, and white RGBW display apparatus, the apparatus including:
the high saturation pixel determining module is used for determining high saturation pixels in a target image, wherein the saturation of the high saturation pixels is greater than a preset saturation threshold, and the brightness values of the high saturation pixels are greater than a brightness threshold;
a high-brightness pixel determination module, configured to determine a high-brightness pixel located in a neighborhood of the high-saturation pixel and a feature value of the high-brightness pixel, where a saturation of the high-brightness pixel is less than or equal to the saturation threshold, and a brightness value of the high-brightness pixel is greater than the brightness threshold;
and the target pixel determining module is used for marking the pixel of which the difference value between the characteristic value and the characteristic value of the high-brightness pixel is smaller than a preset characteristic value difference threshold as a target pixel of which the brightness is to be reduced.
Optionally, the method further includes: the format conversion module is used for converting the to-be-processed image in the RGB format into the Lab format;
the characteristic value calculating module is used for calculating the characteristic value of each pixel in the image to be processed, wherein the characteristic value of each pixel is the arithmetic square root of the sum of squares of the L value, the a value and the b value which are respectively equal-interval quantization values;
and the segmentation module is used for obtaining a target image of at least one object included in the image to be processed by segmentation according to the characteristic values of the pixels, wherein the difference value of the characteristic values of the pixels in each target image is smaller than a preset characteristic value difference threshold value.
Optionally, the high-brightness pixel determination module is specifically configured to: executing the step of determining high-brightness pixels located in the neighborhood of the high-saturation pixels and the characteristic values of the high-brightness pixels when the number of the high-saturation pixels is greater than a preset number threshold;
the device further comprises a termination module, wherein the termination module is used for ending the process under the condition that the number of the high saturation pixels is not larger than a preset number threshold.
Optionally, the high-luminance pixel determining module includes:
a first binarization image establishing sub-module, configured to establish a first binarization image of the target image, where in the first binarization image, brightness of a highly saturated pixel is a first brightness value, brightness of a non-highly saturated pixel is a second brightness value, the non-highly saturated pixel is a pixel other than the highly saturated pixel, and the first brightness value and the second brightness value are not equal to each other;
the removing submodule is used for carrying out kernel expansion on the basis of the high-saturation pixels in the first binary image and removing isolated pixel areas with the size smaller than a preset size threshold value in the first binary image;
and a high-brightness pixel determination submodule, configured to use, as a high-brightness pixel, a pixel in a neighborhood of a pixel in the first binary image, where a brightness value of the pixel is the first brightness value, and a brightness value of the pixel is greater than the brightness threshold, where one of the pixels is reserved as the high-brightness pixel when there are a plurality of pixels in the neighborhood of one highly saturated pixel, where the pixels have the same feature value and the brightness value of the pixel is greater than the brightness threshold.
Optionally, the method further includes: the second binary image establishing module is used for establishing a second binary image of the target image, wherein in the second binary image, the brightness of a target pixel is a third brightness value, the brightness of a non-target pixel is a fourth brightness value, and the non-target pixel is a pixel except the target pixel;
a transition processing module, configured to perform transition processing on a transition region where the target pixel and the non-target pixel are adjacent to each other, so that a luminance value of a pixel in the transition region is between the third luminance value and the fourth luminance value;
and a brightness determining module, configured to determine a brightness reduction degree of the pixel in the transition region according to the brightness value of the pixel in the transition region, where the brightness reduction degree of the pixel in the transition region increases with an increase in a difference between the brightness value and the third brightness value.
According to the embodiment of the invention, the high-saturation pixels in the image are determined, then the high-brightness pixels in the neighborhood of the high-saturation pixels are determined, and the brightness of the pixels with the same characteristic value as the high-brightness pixels is reduced, so that the possibility of color distortion is reduced, the brightness loss is reduced, and the display effect is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a flow chart of an image processing method according to an embodiment of the present invention;
FIG. 2 is an image to be processed in an embodiment of the invention;
FIG. 3 is a segmentation result of the image shown in FIG. 2;
FIG. 4 is a first binarized graph of the image shown in FIG. 2;
FIG. 5 is a second binarized map of the image shown in FIG. 2;
FIG. 6 is a result of a transition process for the image shown in FIG. 5;
fig. 7 is a block diagram of an image processing apparatus according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides an image processing method.
The technical scheme of the embodiment is mainly applied to processing the image in the red, green, blue and white (RGB) format displayed on the red, green, blue and white (RGBW) display device.
In the process of implementing the technical solution of the present application, it is found that, when an image in RGB format is displayed on a display device in RGBW mode, color and brightness of the image are a pair of contradictory problems, there is a simultaneous contrast phenomenon in RGBW, and a hue of the image does not keep constant when relative brightness changes, that is, color of a pixel is affected by peripheral brightness, and when brightness near a high-saturation pixel is too high, color deteriorates, which is mainly because the RGBW display device displays a high-saturation picture, brightness is relatively low, and when a high-brightness picture is displayed, since transmittance of a W sub-pixel is relatively high, display brightness is relatively high, and when the image simultaneously includes high-saturation content and high-brightness content, color distortion occurs.
As shown in fig. 1, in one embodiment, the image processing method includes the steps of:
step 101: highly saturated pixels in the target image are determined.
In this embodiment, the saturation of the high saturation pixel is greater than the preset saturation threshold, and the brightness value of the high saturation pixel is greater than the brightness threshold.
In some embodiments, after step 101, the method further includes:
if the number of the high saturation pixels is larger than a preset number threshold, executing the following step 102;
and ending the process under the condition that the number of the high saturation pixels is not more than a preset number threshold.
In this embodiment, when the number of the high saturation pixels is large, it is considered that the above simultaneous contrast phenomenon occurs, at this time, it is necessary to further mark the high luminance pixels and determine the pixels whose luminance needs to be reduced, so as to improve the display effect, and if the number of the high saturation pixels is relatively small, it is considered that the above simultaneous contrast phenomenon does not occur, the influence on the actual display effect is low, and at this time, no further processing is required.
Step 102: high-luminance pixels located in a neighborhood of the high-saturation pixel and feature values of the high-luminance pixels are determined.
The saturation of the high-brightness pixel is less than or equal to the saturation threshold, and the brightness value of the high-brightness pixel is greater than the brightness threshold. In other words, a high-luminance pixel refers to a pixel having a slightly lower saturation but a relatively higher luminance, i.e., a higher actual luminance, that is, a high luminance pixel and a high-saturation pixel having a higher luminance, and a high saturation pixel having a higher saturation.
In some embodiments, the step 102 specifically includes:
and establishing a first binary image of the target image.
Performing kernel expansion based on the high saturation pixels in the first binary image, and removing isolated pixel regions with the size smaller than a preset size threshold value in the first binary image;
and taking the pixels with the brightness values larger than the brightness threshold value in the neighborhood of the pixels with the brightness values of the first two-valued image as high-brightness pixels, and calculating the characteristic value of each high-brightness pixel.
In the first binary image, the brightness of the high saturation pixel is a first brightness value, and the brightness of the non-high saturation pixel is a second brightness value, wherein the non-high saturation pixel is a pixel except the high saturation pixel, and the first brightness value and the second brightness value are not equal.
For example, as shown in fig. 3, the first luminance value may be set to 255 and the second luminance value may be set to 0, so that the first binarized map is obtained.
In order to determine as accurately as possible the high-brightness pixels that need to be reduced in brightness, the first binarized map obtained is then processed, the high-saturation pixels are first subjected to kernel expansion, and the size and expansion coefficient of the kernel-expanded convolution kernel can be set as desired. In the first binary image after the nuclear expansion, the region corresponding to the high saturation pixel further includes a neighborhood region having a size, and the size of the neighborhood region is influenced by the expansion coefficient set in the nuclear expansion process and increases with the increase of the expansion coefficient.
Next, an isolated pixel region is removed, which refers to a pixel region with a relatively small size, for example, in the first binary image, a region only includes a first luminance value pixel block with a small area, which includes a small number of first luminance value pixels, the pixel block is surrounded by second luminance value pixels, and the number of second luminance value pixels is large, so that the luminance values of the pixels in the first luminance value pixel block with the small area can be adjusted to be high saturation pixels.
Further, after determining the high-luminance pixels, the feature value of each high-luminance pixel is calculated, wherein if there are a plurality of high-luminance pixels having the same feature value in the neighborhood of one high-saturation pixel and having luminance values greater than the luminance threshold, that is, if there are high-luminance pixels having the same feature value, only one of the high-luminance pixels may be retained as the high-luminance pixel, which helps to reduce the amount of calculation.
Step 103: and marking the pixel of which the difference value between the characteristic value and the characteristic value of the high-brightness pixel is smaller than a preset characteristic value difference threshold as a target pixel of which the brightness is to be reduced.
According to the embodiment of the invention, the high-saturation pixels in the image are determined, then the high-brightness pixels in the neighborhood of the high-saturation pixels are determined, and the brightness of the pixels with the same characteristic value as the high-brightness pixels is reduced, so that the possibility of color distortion is reduced, the brightness loss is reduced, and the display effect is improved.
In some embodiments, before step 101, the method further comprises:
converting the to-be-processed image in the RGB format into a Lab format;
calculating the characteristic value of each pixel in the image to be processed;
and obtaining a target image of at least one object included in the image to be processed according to the characteristic value segmentation of the pixels, wherein the difference value of the characteristic value of each pixel in each target image is smaller than a preset characteristic value difference value threshold.
In this embodiment, an image in RGB format to be displayed is first converted into Lab format to calculate a characteristic value, and the Lab mode is composed of L, a and b channels, where the L channel is brightness, a and b are color channels, the color included in the a channel is from dark green (low brightness value) to gray (medium brightness value) to bright pink red (high brightness value), and the color included in the b channel is from dark blue (low brightness value) to gray (medium brightness value) to yellow (high brightness value). The pixel conversion from the RGB mode to the Lab mode can refer to the related art, and is not further limited herein.
Next, the characteristic value of the pixel is calculated, and in the present embodiment, the characteristic value of the pixel is the arithmetic square root of the sum of squares of the L value, the a value, and the b value, respectively, of the equally spaced quantized values. The equally spaced quantized values refer to the L values of the sub-pixels of different colors being equally divided into equal parts, respectively, so as to reduce the size of the quantized values. To enlarge the difference, the squares of the equally spaced quantized values are further squared and the arithmetic square root of the sum is calculated as the characteristic value of the pixel.
In the present embodiment, the characteristic value T ═ L/52+(a/12)2+(b/12)2]1/2。
In the above formula, L, a and b are the values of three Lab channels, respectively, in this embodiment, L, a and b are quantized equally into 5 segments, 12 segments and 12 segments, respectively, then a square value is taken to enlarge the difference, and finally, the arithmetic square root is taken as the characteristic value of the pixel.
In this embodiment, the characteristic value T [ (70/5) can be calculated by substituting the above formula, for example, by L70, a 120, and b 962+(120/12)2+(96/12)2]1/2T is calculated to be about 19 as the characteristic value of the pixel.
Referring to fig. 1 and fig. 2, next, the image to be processed is segmented according to the calculated feature values, in this embodiment, the pixels with the closer feature values are considered as pixels of the same type of object, and are further segmented into the same object, so that the image to be processed can be segmented to obtain the target image corresponding to the object included therein.
It will be appreciated that the number of objects included in an image may be one or more and that, correspondingly, the segmented image comprises a target image of one or more objects.
In some embodiments, after step 103, the method further comprises:
establishing a second binary image of the target image;
performing transition processing on a transition region where the target pixel and the non-target pixel are adjacent to each other, so that the brightness value of the pixel in the transition region is between the third brightness value and the fourth brightness value;
and determining the brightness reduction degree of the pixels in the transition region according to the brightness values of the pixels in the transition region.
As shown in fig. 5, in the present embodiment, a second binary map is further created in which the luminance of the target pixel is the third luminance value, the luminance of the non-target pixel is the fourth luminance value, and the non-target pixel is a pixel other than the target pixel. For example, the third luminance value may be set to 255 and the fourth luminance value may be set to 0, thereby obtaining the second binary map.
As shown in fig. 6, transition processing is performed on the boundary region, or transition region, of the pixels with different brightness in the binary image to improve the continuity of the display effect, so that the brightness is uniformly transitioned, and the influence of sudden brightness change on the display effect is avoided.
In practice, the second binary image may be processed by morphological processing, edge feathering, or the like, such that the luminance value of the pixel in the processed transition region is between the third luminance value and the fourth luminance value.
In this embodiment, the brightness reduction degree of the pixels in the transition region increases with the increase of the difference between the brightness value and the third brightness value, and it can be understood that the brightness value of the pixels in the transition region gradually changes from the third brightness value to the fourth brightness value along the direction from the target pixel to the non-target pixel, and the brightness reduction coefficient of the pixels in the transition region gradually decreases along the direction, so that the actual display brightness gradually decreases along the direction, which is helpful for making the actual display effect continuously change and making the actual display brightness uniformly transition.
The embodiment of the invention provides an image processing device which is applied to an image in a red, green, blue and Red (RGB) format displayed on a red, green, blue and white (RGBW) display device.
As shown in fig. 7, in one embodiment, the image processing apparatus 700 includes:
a high saturation pixel determining module 701, configured to determine a high saturation pixel in a target image, where a saturation of the high saturation pixel is greater than a preset saturation threshold, and a brightness value of the high saturation pixel is greater than a brightness threshold;
a high-brightness pixel determination module 702, configured to determine a high-brightness pixel located in a neighborhood of the high-saturation pixel and a feature value of the high-brightness pixel, where a saturation of the high-brightness pixel is less than or equal to the saturation threshold, and a brightness value of the high-brightness pixel is greater than the brightness threshold;
a target pixel determining module 703, configured to mark, as a target pixel to be brightness reduced, a pixel whose difference between the feature value and the feature value of the high-brightness pixel is smaller than a preset feature value difference threshold.
In some of these embodiments, further comprising: the format conversion module is used for converting the to-be-processed image in the RGB format into the Lab format;
the characteristic value calculating module is used for calculating the characteristic value of each pixel in the image to be processed, wherein the characteristic value of each pixel is the arithmetic square root of the sum of squares of the L value, the a value and the b value which are respectively equal-interval quantization values;
and the segmentation module is used for obtaining a target image of at least one object included in the image to be processed by segmentation according to the characteristic values of the pixels, wherein the difference value of the characteristic values of the pixels in each target image is smaller than a preset characteristic value difference threshold value.
In some embodiments, the high-luminance pixel determination module 702 is specifically configured to: executing the step of determining high-brightness pixels located in the neighborhood of the high-saturation pixels and the characteristic values of the high-brightness pixels when the number of the high-saturation pixels is greater than a preset number threshold;
the device further comprises a termination module, wherein the termination module is used for ending the process under the condition that the number of the high saturation pixels is not larger than a preset number threshold.
In some of these embodiments, the high brightness pixel determination module 702 comprises:
a first binarization image establishing sub-module, configured to establish a first binarization image of the target image, where in the first binarization image, luminance of a highly saturated pixel is a first luminance value, and luminance of a non-highly saturated pixel is a second luminance value, where the non-highly saturated pixel is a pixel other than the highly saturated pixel, and the first luminance value and the second luminance value are not equal to each other;
the removing submodule is used for carrying out kernel expansion on the basis of the high-saturation pixels in the first binary image and removing isolated pixel areas with the size smaller than a preset size threshold value in the first binary image;
and a high-brightness pixel determination submodule, configured to use, as a high-brightness pixel, a pixel in a neighborhood of a pixel in the first binary image, where a brightness value of the pixel is the first brightness value, and a brightness value of the pixel is greater than the brightness threshold, where one of the pixels is reserved as the high-brightness pixel when there are a plurality of pixels in the neighborhood of one highly saturated pixel, where the pixels have the same feature value and the brightness value of the pixel is greater than the brightness threshold.
In some of these embodiments, further comprising: the second binary image establishing module is used for establishing a second binary image of the target image, wherein in the second binary image, the brightness of a target pixel is a third brightness value, the brightness of a non-target pixel is a fourth brightness value, and the non-target pixel is a pixel except the target pixel;
a transition processing module, configured to perform transition processing on a transition region where the target pixel and the non-target pixel are adjacent to each other, so that a luminance value of a pixel in the transition region is between the third luminance value and the fourth luminance value;
and a brightness determining module, configured to determine a brightness reduction degree of the pixel in the transition region according to the brightness value of the pixel in the transition region, where the brightness reduction degree of the pixel in the transition region increases with an increase in a difference between the brightness value and the third brightness value.
The image processing apparatus according to the embodiment of the present invention can implement the steps of the above-mentioned image processing method embodiment, and can implement the same or similar technical effects, which are not described herein again.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An image processing method applied to an image in a red, green, blue, RGB format displayed on a red, green, blue, white, RGBW display device, the method comprising the steps of:
determining high saturation pixels in a target image, wherein the saturation of the high saturation pixels is greater than a preset saturation threshold, and the brightness values of the high saturation pixels are greater than a brightness threshold;
determining high-brightness pixels located in a neighborhood of the high-saturation pixel and characteristic values of the high-brightness pixels, wherein the saturation of the high-brightness pixels is less than or equal to the saturation threshold, and the brightness value of the high-brightness pixels is greater than the brightness threshold;
and marking the pixel of which the difference value between the characteristic value and the characteristic value of the high-brightness pixel is smaller than a preset characteristic value difference threshold as a target pixel of which the brightness is to be reduced.
2. The method of claim 1, wherein prior to determining the highly saturated pixel in the target image, the method further comprises:
converting the to-be-processed image in the RGB format into a Lab format;
calculating the characteristic value of each pixel in the image to be processed, wherein the characteristic value of each pixel is the arithmetic square root of the sum of squares of the L value, the a value and the b value of the equal-interval quantization value respectively;
and obtaining a target image of at least one object included in the image to be processed according to the characteristic value segmentation of the pixels, wherein the difference value of the characteristic value of each pixel in each target image is smaller than a preset characteristic value difference value threshold.
3. The method of claim 1, wherein after determining the highly saturated pixel in the target image, further comprising:
executing the step of determining high-brightness pixels located in the neighborhood of the high-saturation pixels and the characteristic values of the high-brightness pixels when the number of the high-saturation pixels is greater than a preset number threshold;
and ending the process under the condition that the number of the high saturation pixels is not more than a preset number threshold.
4. The method of claim 1, wherein determining high-luminance pixels located in a neighborhood of the high-saturation pixel and their eigenvalues comprises:
establishing a first binary image of the target image, wherein in the first binary image, the brightness of a high-saturation pixel is a first brightness value, the brightness of a non-high-saturation pixel is a second brightness value, the non-high-saturation pixel is a pixel except the high-saturation pixel, and the first brightness value and the second brightness value are not equal;
performing kernel expansion based on the high saturation pixels in the first binary image, and removing isolated pixel regions with the size smaller than a preset size threshold value in the first binary image;
and taking the pixels with the brightness values larger than the brightness threshold value in the neighborhood of the pixels with the brightness values larger than the first brightness value in the first binary image as high-brightness pixels, and calculating the characteristic value of each high-brightness pixel, wherein one of the pixels is kept as the high-brightness pixel under the condition that the neighborhood of one high-saturation pixel has the same characteristic value and the number of the pixels with the brightness values larger than the brightness threshold value is multiple.
5. The method according to claim 4, wherein after marking the pixel with the difference value between the characteristic value and the characteristic value of the high-brightness pixel smaller than the preset characteristic value difference threshold as the target pixel with the brightness to be reduced, the method comprises:
establishing a second binary image of the target image, wherein in the second binary image, the brightness of a target pixel is a third brightness value, the brightness of a non-target pixel is a fourth brightness value, and the non-target pixel is a pixel except the target pixel;
performing transition processing on a transition region where the target pixel and the non-target pixel are adjacent to each other, so that the brightness value of the pixel in the transition region is between the third brightness value and the fourth brightness value;
determining a degree of luminance reduction of the pixels in the transition region according to the luminance values of the pixels in the transition region, wherein the degree of luminance reduction of the pixels in the transition region increases as a difference between the luminance values and the third luminance value increases.
6. An image processing apparatus applied to an image in a red, green, blue, and RGB format displayed on a red, green, blue, and white (RGBW) display apparatus, the apparatus comprising:
the high saturation pixel determining module is used for determining high saturation pixels in a target image, wherein the saturation of the high saturation pixels is greater than a preset saturation threshold, and the brightness values of the high saturation pixels are greater than a brightness threshold;
a high-brightness pixel determination module, configured to determine a high-brightness pixel located in a neighborhood of the high-saturation pixel and a feature value of the high-brightness pixel, where a saturation of the high-brightness pixel is less than or equal to the saturation threshold, and a brightness value of the high-brightness pixel is greater than the brightness threshold;
and the target pixel determining module is used for marking the pixel of which the difference value between the characteristic value and the characteristic value of the high-brightness pixel is smaller than a preset characteristic value difference threshold as a target pixel of which the brightness is to be reduced.
7. The apparatus of claim 6, further comprising:
the format conversion module is used for converting the to-be-processed image in the RGB format into the Lab format;
the characteristic value calculating module is used for calculating the characteristic value of each pixel in the image to be processed, wherein the characteristic value of each pixel is the arithmetic square root of the sum of squares of the L value, the a value and the b value which are respectively equal-interval quantization values;
and the segmentation module is used for obtaining a target image of at least one object included in the image to be processed by segmentation according to the characteristic values of the pixels, wherein the difference value of the characteristic values of the pixels in each target image is smaller than a preset characteristic value difference threshold value.
8. The apparatus of claim 6, wherein the high-luminance pixel determination module is specifically configured to: executing the step of determining high-brightness pixels located in the neighborhood of the high-saturation pixels and the characteristic values of the high-brightness pixels when the number of the high-saturation pixels is greater than a preset number threshold;
the device further comprises a termination module, wherein the termination module is used for ending the process under the condition that the number of the high saturation pixels is not larger than a preset number threshold.
9. The apparatus of claim 6, wherein the high luminance pixel determination module comprises:
a first binarization image establishing sub-module, configured to establish a first binarization image of the target image, where in the first binarization image, brightness of a highly saturated pixel is a first brightness value, brightness of a non-highly saturated pixel is a second brightness value, the non-highly saturated pixel is a pixel other than the highly saturated pixel, and the first brightness value and the second brightness value are not equal to each other;
the removing submodule is used for carrying out kernel expansion on the basis of the high-saturation pixels in the first binary image and removing isolated pixel areas with the size smaller than a preset size threshold value in the first binary image;
and a high-brightness pixel determination submodule, configured to use, as a high-brightness pixel, a pixel in a neighborhood of a pixel in the first binary image, where a brightness value of the pixel is the first brightness value, and a brightness value of the pixel is greater than the brightness threshold, where one of the pixels is reserved as the high-brightness pixel when there are a plurality of pixels in the neighborhood of one highly saturated pixel, where the pixels have the same feature value and the brightness value of the pixel is greater than the brightness threshold.
10. The apparatus of claim 9, further comprising:
the second binary image establishing module is used for establishing a second binary image of the target image, wherein in the second binary image, the brightness of a target pixel is a third brightness value, the brightness of a non-target pixel is a fourth brightness value, and the non-target pixel is a pixel except the target pixel;
a transition processing module, configured to perform transition processing on a transition region where the target pixel and the non-target pixel are adjacent to each other, so that a luminance value of a pixel in the transition region is between the third luminance value and the fourth luminance value;
and a brightness determining module, configured to determine a brightness reduction degree of the pixel in the transition region according to the brightness value of the pixel in the transition region, where the brightness reduction degree of the pixel in the transition region increases with an increase in a difference between the brightness value and the third brightness value.
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