CN112927153B - Image processing method and device - Google Patents
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- 238000000034 method Methods 0.000 claims description 15
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T2207/10—Image acquisition modality
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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 larger than a preset saturation threshold, and the brightness value of the high-saturation pixels is larger than a brightness threshold; determining a high-brightness pixel positioned in the neighborhood of the high-saturation pixel and a characteristic value of the high-brightness pixel, wherein the saturation of the high-brightness pixel is smaller than or equal to the saturation threshold value, and the brightness value of the high-brightness pixel is larger than the brightness threshold value; and marking the pixel with the difference value of the characteristic value and the characteristic value of the high-brightness pixel smaller than a preset characteristic value difference threshold value as a target pixel with brightness to be reduced. The embodiment of the invention reduces the possibility of color distortion, reduces 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 comprises red, green, blue and white sub-pixels, and the W sub-pixels have higher light transmittance, so that the display brightness is improved, and the power consumption is saved. In the related art, an image in RGB (red, green and blue) format is generally converted into a signal matched to an RGBW display device by a specific mapping algorithm, wherein the related mapping algorithm mainly aims at increasing the pixel value of the W sub-pixel. In some cases, if the pixel value of the W subpixel is too high, the visual effect of the subpixels of other colors may be diluted, which may affect the display effect.
Disclosure of Invention
The embodiment of the invention provides an image processing method and device, which are used for solving the problem that the display effect is affected by too high 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 RGB format displayed on an RGB display device, the method including the steps of:
determining high-saturation pixels in a target image, wherein the saturation of the high-saturation pixels is larger than a preset saturation threshold, and the brightness value of the high-saturation pixels is larger than a brightness threshold;
Determining a high-brightness pixel positioned in the neighborhood of the high-saturation pixel and a characteristic value of the high-brightness pixel, wherein the saturation of the high-brightness pixel is smaller than or equal to the saturation threshold value, and the brightness value of the high-brightness pixel is larger than the brightness threshold value;
and marking the pixel with the difference value of the characteristic value and the characteristic value of the high-brightness pixel smaller than a preset characteristic value difference threshold value as a target pixel with brightness to be reduced.
Optionally, before the determining the high saturation pixel in the target image, the method further includes:
converting an image to be processed in an 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 quantized values of L value, a value and b value which are respectively at equal intervals;
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 values of the pixels in each target image is smaller than a preset characteristic value difference value threshold value.
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 under the condition that the number of the high-saturation pixels is larger than a preset number threshold;
and ending the flow under the condition that the number of the high-saturation pixels is not larger than a preset number threshold value.
Optionally, the determining the high-brightness pixel located in the neighborhood of the high-saturation pixel and the characteristic value of the high-brightness pixel includes:
Establishing a first binarization map of the target image, wherein in the first binarization map, the brightness of a high saturated pixel is a first brightness value, the brightness of a non-high saturated pixel is a second brightness value, the non-high saturated pixel is a pixel except the high saturated pixel, and the first brightness value and the second brightness value are unequal;
Performing nuclear expansion based on the high-saturation pixels in the first binarization map, and removing isolated pixel areas with sizes smaller than a preset size threshold in the first binarization map;
And taking the pixels with the brightness value larger than the brightness threshold value in the neighborhood of the pixels with the brightness value being the first brightness value in the first binarization graph as high-brightness pixels, and calculating the characteristic value of each high-brightness pixel, wherein one of the pixels with the brightness value larger than the brightness threshold value is reserved as the high-brightness pixel under the condition that the same characteristic value exists in the neighborhood of one high-saturation pixel and the number of the pixels with the brightness value larger than the brightness threshold value is a plurality of.
Optionally, after marking the pixel whose difference value between the feature value and the feature value of the high-brightness pixel is smaller than the preset feature value difference threshold as the target pixel to be reduced in brightness, the method includes:
establishing a second binarization map of the target image, wherein in the second binarization map, 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 brightness reduction degree of the pixels in the transition region according to the brightness values of the pixels in the transition region, wherein the brightness reduction degree of the pixels in the transition region increases with the increase of the difference value between the brightness value and the third brightness value.
In a second aspect, an embodiment of the present invention provides an image processing apparatus applied to an image in RGB format displayed on an RGB display apparatus, the apparatus including:
a high saturation pixel determining module, configured to determine a high saturation pixel in a target image, where the 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 determining 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 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;
And the target pixel determining module is used for marking the pixel with the difference value of the characteristic value and the characteristic value of the high-brightness pixel smaller than a preset characteristic value difference threshold value as the target pixel with the brightness to be reduced.
Optionally, the method further comprises: the format conversion module is used for converting the RGB format image to be processed into Lab format;
The characteristic value calculation module is used for calculating characteristic values of pixels in the image to be processed, wherein the characteristic values of the pixels are arithmetic square roots of square sums of quantized values of L values, a values and b values which are respectively at equal intervals;
The segmentation module is used for obtaining a target image of at least one object included in the image to be processed according to the characteristic values of the pixels in a segmentation mode, wherein the difference value of the characteristic values of the pixels in each target image is smaller than a preset characteristic value difference value threshold value.
Optionally, the high brightness pixel determining 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 under the condition that the number of the high-saturation pixels is larger than a preset number threshold;
The device also comprises a termination module, wherein the termination module is used for ending the flow when the number of the high-saturation pixels is not larger than a preset number threshold value.
Optionally, the high brightness pixel determining module includes:
A first binarization map creating sub-module, configured to create a first binarization map of the target image, where in the first binarization map, a luminance of a high saturated pixel is a first luminance value, a luminance of a non-high saturated pixel is a second luminance value, the non-high saturated pixel is a pixel other than the high saturated pixel, and the first luminance value and the second luminance value are not equal;
the removing submodule is used for performing nuclear expansion based on the high-saturation pixels in the first binarization graph and removing isolated pixel areas with the sizes smaller than a preset size threshold in the first binarization graph;
And the high-brightness pixel determination submodule is used for taking the pixels with the brightness value larger than the brightness threshold value in the neighborhood of the pixels with the brightness value being the first brightness value in the first binarization graph as high-brightness pixels, wherein one of the pixels with the brightness value larger than the brightness threshold value is reserved as the high-brightness pixels under the condition that the same characteristic value exists in the neighborhood of one high-saturation pixel and the number of the pixels with the brightness value larger than the brightness threshold value is a plurality of.
Optionally, the method further comprises: a second binarization map building module, configured to build a second binarization map of the target image, where in the second binarization map, luminance of a target pixel is a third luminance value, luminance of a non-target pixel is a fourth luminance value, and the non-target pixel is a pixel other than 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, so that a luminance value of a pixel in the transition region is between the third luminance value and the fourth luminance value;
And the brightness determining module is used for determining the brightness reduction degree of the pixels in the transition area according to the brightness values of the pixels in the transition area, wherein the brightness reduction degree of the pixels in the transition area increases along with the increase of the difference value between the brightness values 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 that are needed in the description of the embodiments of the present invention will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
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 binarization map of the image shown in FIG. 2;
FIG. 5 is a second binarized plot of the image shown in FIG. 2;
FIG. 6 is a transition processing result of the image shown in FIG. 5;
Fig. 7 is a block diagram of an image processing apparatus according to an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment of the invention provides an image processing method.
The technical scheme of the embodiment is mainly applied to processing images when the images are in red, green and blue RGB format and displayed on the red, green and blue RGBW display device.
In implementing the technical scheme of the application, the related technical personnel find that when an image in an RGB format is displayed on a display device in an RGBW mode, the color and the brightness of the image are a pair of contradictory problems, a simultaneous contrast phenomenon exists in RGBW, the hue of the image is not kept constant when the relative brightness changes, namely, the color of a pixel is influenced by peripheral brightness, when the brightness near a high-saturation pixel is too high, the color is degraded, the main reason is that the brightness of the RGBW display device is relatively low when the high-saturation picture is displayed, and when the high-saturation picture is displayed, the brightness is relatively high due to the fact that the transmittance of a W sub-pixel is large, and color distortion is generated when the high-saturation content and the high-brightness content are simultaneously contained in the image.
As shown in fig. 1, in one embodiment, the image processing method includes the steps of:
Step 101: high saturation pixels in the target image are determined.
In this embodiment, the saturation of the high saturation pixel is greater than a preset saturation threshold, and the luminance value of the high saturation pixel is greater than a luminance threshold.
In some of these embodiments, after step 101, further comprising:
In case the number of high saturation pixels is greater than a preset number threshold, performing the following 102 steps;
and ending the flow under the condition that the number of the high-saturation pixels is not larger than a preset number threshold value.
In this embodiment, when the number of the high saturation pixels is large, the above simultaneous contrast phenomenon is considered to occur, at this time, it is necessary to further mark the high brightness pixels and determine the pixels whose brightness needs to be reduced, so as to improve the display effect, whereas if the number of the high saturation pixels is relatively small, it is considered that the above simultaneous contrast phenomenon does not occur, and the influence on the actual display effect is low, at this time, no further processing is necessary.
Step 102: a high-luminance pixel located in a neighborhood of the high-saturation pixel and a feature value of the high-luminance pixel 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, the high-luminance pixel refers to a saturation slightly lower, but a luminance is relatively higher, that is, an actual luminance is higher, that is, the luminance of the high-luminance pixel and the high-saturation pixel is higher, and the saturation region of the high-luminance pixel is higher than the saturation of the high-saturation pixel.
In some of these embodiments, the step 102 specifically includes:
A first binarization map of the target image is established.
Performing nuclear expansion based on the high-saturation pixels in the first binarization map, and removing isolated pixel areas with sizes smaller than a preset size threshold in the first binarization map;
And taking pixels with the brightness value larger than the brightness threshold value in the neighborhood of the pixels with the brightness value being the first brightness value in the first binarization graph as high-brightness pixels, and calculating the characteristic value of each high-brightness pixel.
In the first binarization map, the luminance of the high saturated pixel is a first luminance value, and the luminance of the non-high saturated pixel is a second luminance value, wherein the non-high saturated pixel is a pixel other than the high saturated pixel, and the first luminance value and the second luminance 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 to 0, so that the first binarized map is obtained.
In order to determine the high-luminance pixels, which require a reduction in luminance, as accurately as possible, the obtained first binarized map is then processed, and the high-saturation pixels are first subjected to kernel expansion, and the size and expansion coefficient of the kernel-expanded convolution kernel may be set as desired. In the first binarization map after the nuclear expansion, the region corresponding to the high saturation pixel further includes a neighborhood having a certain size, and the size of the neighborhood is affected by the expansion coefficient set in the nuclear expansion process and increases with the increase of the expansion coefficient.
The isolated pixel region is then removed, where the isolated pixel region refers to a relatively small-sized pixel region, for example, in the first binarization map, a region includes only a small-sized first luminance value pixel block, which includes a small number of first luminance value pixels, surrounded by second luminance value pixels, and the second luminance value pixels are larger in number, so that the luminance values of the pixels in the small-sized first luminance value pixel block can be adjusted to be high-saturation pixels.
Further, after the high-luminance pixels are determined, the feature value of each high-luminance pixel is calculated, wherein if there are the same feature value in the neighborhood of one high-saturation pixel and the number of pixels whose luminance value is greater than the luminance threshold is plural, that is, if there are high-luminance pixels whose feature values are the same, only one of them can be retained as the high-luminance pixel, which contributes to the reduction of the calculation amount.
Step 103: and marking the pixel with the difference value of the characteristic value and the characteristic value of the high-brightness pixel smaller than a preset characteristic value difference threshold value as a target pixel with brightness 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 of these embodiments, prior to step 101, the method further comprises:
converting an image to be processed in an RGB format into a Lab format;
calculating characteristic values of pixels 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 values of the pixels in each target image is smaller than a preset characteristic value difference value threshold value.
In this embodiment, firstly, an image in RGB format to be displayed is converted into Lab format, so as to calculate a characteristic value, the Lab mode is composed of L, a and b channels, wherein L channels are brightness, a and b are color channels, the a channel includes colors from dark green (low brightness value) to gray (medium brightness value) to bright pink (high brightness value), and the b channel includes colors from dark blue (low brightness value) to gray (medium brightness value) to yellow (high brightness value). The pixel conversion method from RGB mode to Lab mode can refer to the related art, and is not further limited herein.
Next, the eigenvalue of the pixel is calculated, which in this embodiment is the arithmetic square root of the sum of squares of quantized values of L value, a value, and b value, respectively, at equal intervals. Wherein, the equal interval quantized values refer to that the L values of the sub-pixels with different colors are respectively divided into a plurality of equal parts in average so as to reduce the size of the quantized values. To expand the difference, the square of each equally spaced quantized value is further taken and the arithmetic square root of its sum is calculated as the eigenvalue of that pixel.
In this embodiment, the characteristic value T= [ (L/5) 2+(a/12)2+(b/12)2]1/2.
In the above formula, L, a and b are values of three channels of Lab, in this embodiment, L, a and b are quantized and divided into 5 segments, 12 segments and 12 segments at equal intervals, then the 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, taking l=70, a=120, and b=96 as an example, the characteristic value t= [ (70/5) 2+(120/12)2+(96/12)2]1/2 can be calculated by taking the above formula, and T is 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 relatively close feature values are considered to be 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 a target image corresponding to the object included therein.
It should be appreciated that the number of objects included in an image may be one or more, and that the segmented image may include a target image of one or more objects, accordingly.
In some of these embodiments, after step 103, comprising:
Establishing a second binarization map 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 binarization map is further created, in which the luminance of the target pixel is a third luminance value, the luminance of the non-target pixel is a 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 binarized map.
As shown in fig. 6, the boundary areas or transition areas of pixels with different brightness in the binary image are subjected to transition treatment, so as to improve the continuity of the display effect, make the brightness transition uniformly, and avoid the influence of the brightness abrupt change on the display effect.
In implementation, the second binarization map may be processed by morphological processing, an edge feathering algorithm, or the like, so that the luminance value of the pixel in the transition region after the processing is located between the third luminance value and the fourth luminance value.
In this embodiment, the brightness decrease 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 is 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 decrease coefficient of the pixels in the transition region gradually decreases along the direction, so that the actual display brightness gradually decreases along the above direction, contributing to continuous change of the actual display effect, and uniform transition of the actual display brightness.
The embodiment of the invention provides an image processing device which is applied to an image in red, green and blue RGB format displayed on an 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 luminance value of the high saturation pixel is greater than a luminance threshold;
A high-brightness pixel determining 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;
The target pixel determining module 703 is configured to mark 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 as a target pixel to be brightness-reduced.
In some of these embodiments, further comprising: the format conversion module is used for converting the RGB format image to be processed into Lab format;
The characteristic value calculation module is used for calculating characteristic values of pixels in the image to be processed, wherein the characteristic values of the pixels are arithmetic square roots of square sums of quantized values of L values, a values and b values which are respectively at equal intervals;
The segmentation module is used for obtaining a target image of at least one object included in the image to be processed according to the characteristic values of the pixels in a segmentation mode, wherein the difference value of the characteristic values of the pixels in each target image is smaller than a preset characteristic value difference value threshold value.
In some embodiments, the high brightness 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 under the condition that the number of the high-saturation pixels is larger than a preset number threshold;
The device also comprises a termination module, wherein the termination module is used for ending the flow when the number of the high-saturation pixels is not larger than a preset number threshold value.
In some of these embodiments, the high brightness pixel determination module 702 includes:
A first binarization map creation sub-module configured to create a first binarization map of the target image, wherein in the first binarization map, a luminance of a high saturated pixel is a first luminance value, and a luminance of a non-high saturated pixel is a second luminance value, wherein the non-high saturated pixel is a pixel other than the high saturated pixel, and the first luminance value and the second luminance value are not equal;
the removing submodule is used for performing nuclear expansion based on the high-saturation pixels in the first binarization graph and removing isolated pixel areas with the sizes smaller than a preset size threshold in the first binarization graph;
And the high-brightness pixel determination submodule is used for taking the pixels with the brightness value larger than the brightness threshold value in the neighborhood of the pixels with the brightness value being the first brightness value in the first binarization graph as high-brightness pixels, wherein one of the pixels with the brightness value larger than the brightness threshold value is reserved as the high-brightness pixels under the condition that the same characteristic value exists in the neighborhood of one high-saturation pixel and the number of the pixels with the brightness value larger than the brightness threshold value is a plurality of.
In some of these embodiments, further comprising: a second binarization map building module, configured to build a second binarization map of the target image, where in the second binarization map, luminance of a target pixel is a third luminance value, luminance of a non-target pixel is a fourth luminance value, and the non-target pixel is a pixel other than 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, so that a luminance value of a pixel in the transition region is between the third luminance value and the fourth luminance value;
And the brightness determining module is used for determining the brightness reduction degree of the pixels in the transition area according to the brightness values of the pixels in the transition area, wherein the brightness reduction degree of the pixels in the transition area increases along with the increase of the difference value between the brightness values and the third brightness value.
The image processing device according to the embodiment of the present invention can implement each step of the embodiment of the image processing method, and can implement the same or similar technical effects, which are not described herein.
The foregoing is merely illustrative 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 think about variations or substitutions within the technical scope of the present invention, and the invention should be covered. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (10)
1. An image processing method applied to an image of RGB format displayed on an RGB 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 larger than a preset saturation threshold, and the brightness value of the high-saturation pixels is larger than a brightness threshold;
Determining a high-brightness pixel positioned in the neighborhood of the high-saturation pixel and a characteristic value of the high-brightness pixel, wherein the saturation of the high-brightness pixel is smaller than or equal to the saturation threshold value, and the brightness value of the high-brightness pixel is larger than the brightness threshold value;
and marking the pixel with the difference value of the characteristic value and the characteristic value of the high-brightness pixel smaller than a preset characteristic value difference threshold value as a target pixel with brightness to be reduced.
2. The method of claim 1, wherein prior to the determining the high saturation pixels in the target image, the method further comprises:
converting an image to be processed in an 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 quantized values of L value, a value and b value which are respectively at equal intervals;
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 values of the pixels in each target image is smaller than a preset characteristic value difference value threshold value.
3. The method of claim 1, wherein after determining the high saturation pixels 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 under the condition that the number of the high-saturation pixels is larger than a preset number threshold;
and ending the flow under the condition that the number of the high-saturation pixels is not larger than a preset number threshold value.
4. The method of claim 1, wherein the determining the high luminance pixels and the eigenvalues of the high luminance pixels located in the neighborhood of the high saturation pixel comprises:
Establishing a first binarization map of the target image, wherein in the first binarization map, the brightness of a high saturated pixel is a first brightness value, the brightness of a non-high saturated pixel is a second brightness value, the non-high saturated pixel is a pixel except the high saturated pixel, and the first brightness value and the second brightness value are unequal;
Performing nuclear expansion based on the high-saturation pixels in the first binarization map, and removing isolated pixel areas with sizes smaller than a preset size threshold in the first binarization map;
And taking the pixels with the brightness value larger than the brightness threshold value in the neighborhood of the pixels with the brightness value being the first brightness value in the first binarization graph as high-brightness pixels, and calculating the characteristic value of each high-brightness pixel, wherein one of the pixels with the brightness value larger than the brightness threshold value is reserved as the high-brightness pixel under the condition that the same characteristic value exists in the neighborhood of one high-saturation pixel and the number of the pixels with the brightness value larger than the brightness threshold value is a plurality of.
5. The method according to claim 4, wherein after marking a pixel having a difference value between the feature value and the feature value of the high-luminance pixel smaller than a preset feature value difference threshold as a target pixel to be luminance reduced, comprising:
establishing a second binarization map of the target image, wherein in the second binarization map, 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 brightness reduction degree of the pixels in the transition region according to the brightness values of the pixels in the transition region, wherein the brightness reduction degree of the pixels in the transition region increases with the increase of the difference value between the brightness value and the third brightness value.
6. An image processing apparatus, which is applied to an image of RGB format displayed on an RGB display apparatus, the apparatus comprising:
a high saturation pixel determining module, configured to determine a high saturation pixel in a target image, where the 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 determining 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 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;
And the target pixel determining module is used for marking the pixel with the difference value of the characteristic value and the characteristic value of the high-brightness pixel smaller than a preset characteristic value difference threshold value as the target pixel with the brightness to be reduced.
7. The apparatus as recited in claim 6, further comprising:
The format conversion module is used for converting the RGB format image to be processed into Lab format;
The characteristic value calculation module is used for calculating characteristic values of pixels in the image to be processed, wherein the characteristic values of the pixels are arithmetic square roots of square sums of quantized values of L values, a values and b values which are respectively at equal intervals;
The segmentation module is used for obtaining a target image of at least one object included in the image to be processed according to the characteristic values of the pixels in a segmentation mode, wherein the difference value of the characteristic values of the pixels in each target image is smaller than a preset characteristic value difference value threshold value.
8. The apparatus of claim 6, wherein 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 under the condition that the number of the high-saturation pixels is larger than a preset number threshold;
The device also comprises a termination module, wherein the termination module is used for ending the flow when the number of the high-saturation pixels is not larger than a preset number threshold value.
9. The apparatus of claim 6, wherein the high brightness pixel determination module comprises:
A first binarization map creating sub-module, configured to create a first binarization map of the target image, where in the first binarization map, a luminance of a high saturated pixel is a first luminance value, a luminance of a non-high saturated pixel is a second luminance value, the non-high saturated pixel is a pixel other than the high saturated pixel, and the first luminance value and the second luminance value are not equal;
the removing submodule is used for performing nuclear expansion based on the high-saturation pixels in the first binarization graph and removing isolated pixel areas with the sizes smaller than a preset size threshold in the first binarization graph;
And the high-brightness pixel determination submodule is used for taking the pixels with the brightness value larger than the brightness threshold value in the neighborhood of the pixels with the brightness value being the first brightness value in the first binarization graph as high-brightness pixels, wherein one of the pixels with the brightness value larger than the brightness threshold value is reserved as the high-brightness pixels under the condition that the same characteristic value exists in the neighborhood of one high-saturation pixel and the number of the pixels with the brightness value larger than the brightness threshold value is a plurality of.
10. The apparatus as recited in claim 9, further comprising:
A second binarization map building module, configured to build a second binarization map of the target image, where in the second binarization map, luminance of a target pixel is a third luminance value, luminance of a non-target pixel is a fourth luminance value, and the non-target pixel is a pixel other than 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, so that a luminance value of a pixel in the transition region is between the third luminance value and the fourth luminance value;
And the brightness determining module is used for determining the brightness reduction degree of the pixels in the transition area according to the brightness values of the pixels in the transition area, wherein the brightness reduction degree of the pixels in the transition area increases along with the increase of the difference value between the brightness values and the third brightness value.
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