CN114119431A - Image processing method, image processing device, electronic equipment and storage medium - Google Patents

Image processing method, image processing device, electronic equipment and storage medium Download PDF

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CN114119431A
CN114119431A CN202111320162.XA CN202111320162A CN114119431A CN 114119431 A CN114119431 A CN 114119431A CN 202111320162 A CN202111320162 A CN 202111320162A CN 114119431 A CN114119431 A CN 114119431A
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image
brightness
determining
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pixel
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田其冲
李建强
吴有肇
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Shenzhen TCL New Technology Co Ltd
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Shenzhen TCL New Technology Co Ltd
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Priority to PCT/CN2022/120605 priority patent/WO2023082859A1/en
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06T5/90—Dynamic range modification of images or parts thereof
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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Abstract

The embodiment of the application discloses an image processing method and device, electronic equipment and a storage medium. The method comprises the following steps: the electronic equipment acquires a first image, determines a histogram and average pixel brightness corresponding to the first image, and then determines an image type corresponding to the first image according to the histogram and the average pixel brightness; determining a target adjustment type corresponding to the first image according to the image type; and finally, adjusting the brightness value of each pixel of the first image according to the target adjustment type to obtain a second image. Due to the fact that the image type corresponding to the first image is determined in the application, the image can be better adjusted by adopting the adjusting type corresponding to the image type, and therefore the image quality of the image is improved.

Description

Image processing method, image processing device, electronic equipment and storage medium
Technical Field
The present application relates to the field of communications technologies, and in particular, to an image processing method and apparatus, an electronic device, and a storage medium.
Background
In the prior art, for a display picture of a display screen, a single adjustment mode is often adopted to adjust the display picture, but for display pictures of different display scenes, if the single adjustment mode is adopted to adjust different display pictures, the display effect of some display pictures after adjustment is worse.
Disclosure of Invention
The embodiment of the application provides an image processing method and device, electronic equipment and a storage medium. The image processing method can process different image types, thereby improving the image quality.
In a first aspect, an embodiment of the present application provides an image processing method, including:
acquiring a first image, and determining a histogram and average pixel brightness corresponding to the first image;
determining the image type corresponding to the first image according to the histogram and the average pixel brightness;
determining a target adjustment type corresponding to the first image according to the image type;
and adjusting the brightness value of each pixel of the first image according to the target adjustment type to obtain a second image.
In a second aspect, an embodiment of the present application provides an image processing apparatus, including:
the device comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring a first image and determining a histogram and average pixel brightness corresponding to the first image;
the first determining module is used for determining the image type corresponding to the first image according to the histogram and the average pixel brightness;
the second determining module is used for determining a target adjusting type corresponding to the first image according to the image type;
and the adjusting module is used for adjusting the brightness value of each pixel of the first image according to the target adjusting type to obtain a second image.
In a third aspect, an embodiment of the present application provides an electronic device, including a memory storing executable program code, and a processor coupled to the memory; the processor calls the executable program codes stored in the memory to execute the steps in the image processing method provided by the embodiment of the application.
In a fourth aspect, the present application provides a computer-readable storage medium, where the storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to perform the steps in the image processing method provided by the present application.
In the embodiment of the application, the electronic equipment acquires a first image, determines a histogram and average pixel brightness corresponding to the first image, and then determines an image type corresponding to the first image according to the histogram and the average pixel brightness; determining a target adjustment type corresponding to the first image according to the image type; and finally, adjusting the brightness value of each pixel of the first image according to the target adjustment type to obtain a second image. Due to the fact that the image type corresponding to the first image is determined in the application, the image can be better adjusted by adopting the adjusting type corresponding to the image type, and therefore the image quality of the image is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a first flowchart of an image processing method according to an embodiment of the present application.
Fig. 2 is a second flowchart of the image processing method according to the embodiment of the present application.
Fig. 3 is a schematic diagram of a first structure of an image processing apparatus according to an embodiment of the present application.
Fig. 4 is a schematic diagram of a second structure of an image processing apparatus according to an embodiment of the present application.
Fig. 5 is a schematic structural diagram of an electronic device provided in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. 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 application.
In the related art, in order to improve the picture quality displayed on the display screen, it is currently common to adjust the display pictures in all the scenes by using a single picture adjustment method. However, since the scene of the picture in the video is constantly changed, for example, brightness and color of different display areas are changed, the scene of the picture corresponding to the image in different frames may be different. If a single picture adjustment mode is still adopted, the corresponding display quality of the adjusted picture is worse.
For example, if the brightness of the picture is raised alone, and the dark area is not considered, the picture details in the dark area will be lost. If the brightness of the highlight area is to be suppressed alone, this may result in some areas not being sufficiently bright. Resulting in a poor appearance of the final display.
In order to solve the technical problem, embodiments of the present application provide an image processing method, an image processing apparatus, an electronic device, and a storage medium. The image processing method can process different image types, thereby improving the image quality.
It should be noted that the image processing method is applicable to any electronic device capable of processing images, such as a television, a smart phone, a computer, a tablet computer, smart glasses, a head-mounted virtual device, and other electronic devices.
Referring to fig. 1, fig. 1 is a first flow chart of an image processing method according to an embodiment of the present disclosure. The image processing method may include the steps of:
110. a first image is obtained, and a histogram and average pixel brightness corresponding to the first image are determined.
In some embodiments, the electronic device may first acquire an initial image and then perform color space conversion on the initial image to obtain a first image. For example, if the initial image is an image in RGB (Red, Green, Blue) color space, the first image can be obtained by converting the RGB color space of the initial image into YUV color space, where "Y" in the YUV color space represents brightness, "U" and "V" represent chromaticity or Chroma, and the function is to describe the image color and saturation for specifying the color of the pixel.
It should be noted that, the above is only an example, the image format of the first image may be set according to actual requirements, for example, the color space of the first image may be an HSV color space.
In some embodiments, after the first image is acquired, a Histogram (Histogram) may be generated according to the luminance value of each pixel in the first image, where the Histogram is used to measure the distribution of pixels under different luminances, for example, the horizontal axis of the Histogram is luminance and the vertical axis is the number of pixels.
For example, the histogram corresponding to the first image may be determined directly from the luminance component of the Y channel of the first image.
In some embodiments, the electronic device can determine the number of all pixels in the first image and determine a luminance value corresponding to each pixel, and then determine an average pixel luminance using the number of all pixels and the luminance value corresponding to each pixel.
For example, the average pixel luminance is obtained by adding the luminance values of each pixel to obtain a luminance sum and then dividing the luminance sum by the number of all the pixels.
120. And determining the image type corresponding to the first image according to the histogram and the average pixel brightness.
In some embodiments, the electronic device can normalize the histogram and then determine the image type corresponding to the first image based on the normalized histogram and the average pixel intensity.
For example, the electronic device may determine the low luminance ratio, the medium luminance ratio, and the high luminance ratio of the pixel in the first image according to the normalized histogram, and for example, may obtain a probability cumulative distribution function cdf (cumulative Density function) of the image luminance of the first image according to the normalized histogram, so as to determine the low luminance ratio, the medium luminance ratio, and the high luminance ratio of the first image.
In some embodiments, the electronic device may set a low brightness threshold and a high brightness threshold, where the high brightness threshold is greater than the low brightness threshold, determine a range from zero to the low brightness threshold as a low brightness range, determine a range from the low brightness threshold to the high brightness threshold as a medium brightness range, and determine a range from the high brightness threshold to a brightness saturation value as a high brightness range.
And finally, determining a low-brightness ratio, a medium-brightness ratio and a high-brightness ratio according to the number of the pixels in each brightness range and the total number of the pixels of the first image.
In some embodiments, the electronic device can determine the image type corresponding to the first image according to the low luminance ratio, the medium luminance ratio, the high luminance ratio, and the average pixel luminance.
For example, the electronic device determines a first high threshold and a first low threshold corresponding to a low luminance duty ratio, a second high threshold and a second low threshold corresponding to a medium luminance duty ratio, and a third high threshold and a third low threshold corresponding to a high luminance duty ratio. Wherein the first high threshold is greater than the first low threshold, the second high threshold is greater than the second low threshold, and the third high threshold is greater than the third low threshold.
And determining the image type corresponding to the first image according to the first high threshold and the first low threshold, the second high threshold and the second low threshold, the third high threshold and the third low threshold and the average pixel brightness. Wherein the first high threshold and the first low threshold, the second high threshold and the second low threshold, and the third high threshold and the third low threshold may be preset.
For example, the electronic device first determines a preset low average brightness and a preset high average brightness corresponding to the first image, where the preset low average brightness and the preset high average brightness may be preset.
When the electronic device determines that the low-brightness ratio of the first image is greater than or equal to a first high threshold, the medium-brightness ratio of the first image is smaller than a second low threshold, the high-brightness ratio is smaller than a third low threshold, and the average pixel brightness of the first image is smaller than a preset low average brightness, it is determined that the image type corresponding to the first image is the image type of the low-brightness scene.
When the electronic equipment determines that the low-brightness ratio of the first image is greater than or equal to a first low threshold, the medium-brightness ratio of the first image is greater than or equal to a second low threshold, the high-brightness ratio is less than a third low threshold, and the average pixel brightness of the first image is greater than or equal to a preset low-average brightness, the image type corresponding to the first image is determined to be the image type of the low-medium brightness scene.
When the electronic device determines that the low-brightness ratio of the first image is smaller than a first low threshold, the medium-brightness ratio of the first image is larger than or equal to a second high threshold, the high-brightness ratio is smaller than a third low threshold, the average pixel brightness of the first image is larger than or equal to a preset low average brightness, and the average pixel brightness of the first image is smaller than a preset high average brightness, it is determined that the image type corresponding to the first image is the image type of the medium-brightness scene.
When the electronic device determines that the low-brightness ratio of the first image is smaller than a first low threshold, the medium-brightness ratio of the first image is larger than or equal to a second high threshold, the high-brightness ratio is larger than or equal to a third low threshold, the average pixel brightness of the first image is larger than or equal to a preset low average brightness, and the average pixel brightness of the first image is smaller than a preset high average brightness, it is determined that the image type corresponding to the first image is the image type of the medium-high brightness scene.
When the electronic device determines that the low-brightness ratio of the first image is smaller than a first low threshold, the medium-brightness ratio of the first image is smaller than a second low threshold, the high-brightness ratio is larger than or equal to a third high threshold, and the average pixel brightness of the first image is larger than or equal to a preset high average brightness, it is determined that the image type corresponding to the first image is the image type of the high-brightness scene.
When the electronic device determines that the low-brightness ratio of the first image is greater than or equal to a first low threshold, the medium-brightness ratio of the first image is smaller than a second low threshold, the high-brightness ratio is greater than or equal to a third low threshold, the average pixel brightness of the first image is greater than or equal to a preset low average brightness, and the average pixel brightness of the first image is smaller than a preset high average brightness, it is determined that the image type corresponding to the first image is the image type of the low-high brightness scene.
When the electronic device determines that the low-brightness ratio of the first image is greater than or equal to a first low threshold, the medium-brightness ratio of the first image is greater than or equal to a second low threshold, the high-brightness ratio is greater than or equal to a third low threshold, the average pixel brightness of the first image is greater than or equal to a preset low average brightness, and the average pixel brightness of the first image is less than a preset high average brightness, it is determined that the image type corresponding to the first image is the image type of the uniform-brightness scene.
It should be noted that, in practical applications, other image types may also be determined according to the foregoing manner, and the above-mentioned image types are only part of the embodiments provided in this application and are not to be considered as limitations of this application.
130. And determining a target adjustment type corresponding to the first image according to the image type.
In some embodiments, multiple adjustment types may be preset in the electronic device, and the brightness adjustment manner of the first image corresponding to each adjustment type is different.
The electronic device may set a first preset mapping relationship between the image type and the adjustment type, and after the electronic device determines the image type of the first image, the electronic device may determine the target adjustment type corresponding to the first image directly according to the first preset mapping relationship.
140. And adjusting the brightness value of each pixel of the first image according to the target adjustment type to obtain a second image.
In some embodiments, the electronic device may determine a type of an adjustment curve corresponding to the first image according to the target adjustment type, and then adjust a brightness value of each pixel of the first image according to the type of the adjustment curve to obtain the second image.
For example, a database may be preset, a second preset mapping relationship between a plurality of target adjustment types and a plurality of adjustment curve types is stored in the database, and after the electronic device determines the target adjustment type of the first image, the adjustment curve type corresponding to the first image may be determined in the database according to the second preset mapping relationship. And then the electronic equipment adjusts the brightness curve corresponding to the first image according to the type of the adjusting curve, so that a second image is obtained.
In some embodiments, the electronic device may determine a brightness lookup table corresponding to the first image according to the target adjustment type, then determine a mapped brightness value corresponding to each pixel in the first image according to the brightness lookup table, and finally adjust the brightness value of each pixel to the corresponding mapped brightness value to generate the second image.
For example, a brightness lookup table corresponding to each of a plurality of image types is stored in the electronic device. After the image type of the first image is determined, a brightness lookup table corresponding to the image type is determined, and then the electronic device determines a mapping brightness value corresponding to the brightness value of each pixel in the first image through the lookup table. For example, the luminance value of the pixel a is 25, and the mapping luminance value corresponding to the luminance value of the pixel a can be determined to be 50 by the luminance lookup table. By the method, the mapping brightness value corresponding to each pixel in the first image can be determined, and then the brightness value of each pixel in the first image is adjusted to the corresponding mapping brightness value, so that the second image is obtained.
In some embodiments, after acquiring the target adjustment type of the first image, the electronic device may input the target adjustment type into the neural network model, select a corresponding adjustment curve type through the neural network model, and then adjust the brightness curve of the first image according to the adjustment curve type, so that the brightness values of at least some pixels in the first image may be changed, thereby obtaining the second image.
In the embodiment of the application, the electronic equipment acquires a first image, determines a histogram and average pixel brightness corresponding to the first image, and then determines an image type corresponding to the first image according to the histogram and the average pixel brightness; determining a target adjustment type corresponding to the first image according to the image type; and finally, adjusting the brightness value of each pixel of the first image according to the target adjustment type to obtain a second image. Due to the fact that the image type corresponding to the first image is determined in the application, the image can be better adjusted by adopting the adjusting type corresponding to the image type, and therefore the image quality of the image is improved.
For more detailed understanding of the image processing method provided in the embodiment of the present application, please refer to fig. 2, and fig. 2 is a second flowchart of the image processing method provided in the embodiment of the present application. The image processing method may include:
201. the number of pixels in the first image and the brightness value corresponding to each pixel in the first image are obtained.
In some embodiments, the electronic device may first acquire an initial image and then perform color space conversion on the initial image to obtain a first image. For example, if the initial image is an image in an RGB color space, the first image may be obtained by converting the RGB color space of the initial image into a YUV color space.
In some embodiments, the electronic device can obtain the number of pixels in the image and the corresponding luminance value for each pixel in the first image.
202. And determining the average pixel brightness according to the number of the pixels in the first image and the brightness value corresponding to each pixel.
The electronic device may determine the number of all pixels in the first image and determine a luminance value for each pixel, and then determine an average pixel luminance using the number of all pixels and the luminance value for each pixel.
For example, the average pixel luminance is obtained by adding the luminance values of each pixel to obtain a luminance sum and then dividing the luminance sum by the number of all the pixels.
203. The histogram is generated from the luminance value of each pixel.
The electronic device can determine the brightness distribution in different brightness ranges according to the brightness value of each pixel, so as to generate a histogram.
In some embodiments, the electronic device may divide the histogram into a preset number of sub-partitions according to the preset number of partitions, for example, if the preset number of partitions is 32, the histogram may be divided into 32 different sub-partitions.
204. And carrying out normalization processing on the histogram to obtain a normalized histogram.
In some embodiments, the histogram may be normalized by normalizing the luminance values of all pixels in the first image to a luminance range, thereby obtaining a normalized histogram.
For example, a preset brightness range may be set, the preset brightness range is 0 to 255, and the brightness values of all the pixels may be normalized to be within the range of 0 to 255. Thereby obtaining a normalized histogram.
205. And determining the low-brightness ratio, the medium-brightness ratio and the high-brightness ratio of the pixels in the first image according to the normalized histogram.
In some embodiments, after obtaining the normalized histogram corresponding to the first image, the electronic device may obtain a probability cumulative distribution function of the image brightness of the first image according to the normalized histogram. Thereby determining the low, medium and high luminance ratios of the pixels in the first image.
In some embodiments, the electronic device may set a low brightness threshold and a high brightness threshold, where the high brightness threshold is greater than the low brightness threshold, determine a range from zero to the low brightness threshold as a low brightness range, determine a range from the low brightness threshold to the high brightness threshold as a medium brightness range, and determine a range from the high brightness threshold to a brightness saturation value as a high brightness range.
And finally, determining a low-brightness ratio, a medium-brightness ratio and a high-brightness ratio according to the number of the pixels in each brightness range and the total number of the pixels of the first image.
206. And determining a first high threshold and a first low threshold corresponding to the low brightness ratio, a second high threshold and a second low threshold corresponding to the medium brightness ratio, and a third high threshold and a third low threshold corresponding to the high brightness ratio.
In some embodiments, the electronic device determines a first high threshold and a first low threshold for low luminance duty ratio, a second high threshold and a second low threshold for medium luminance duty ratio, and a third high threshold and a third low threshold for high luminance duty ratio. Wherein the first high threshold is greater than the first low threshold, the second high threshold is greater than the second low threshold, and the third high threshold is greater than the third low threshold.
207. And determining the image type corresponding to the first image according to the first high threshold and the first low threshold, the second high threshold and the second low threshold, the third high threshold and the third low threshold and the average pixel brightness.
In some embodiments, the electronic device first determines a preset low average brightness and a preset high average brightness corresponding to the first image, where the preset low average brightness and the preset high average brightness may be preset.
When the electronic device determines that the low-brightness ratio of the first image is greater than or equal to a first high threshold, the medium-brightness ratio of the first image is smaller than a second low threshold, the high-brightness ratio is smaller than a third low threshold, and the average pixel brightness of the first image is smaller than a preset low average brightness, it is determined that the image type corresponding to the first image is the image type of the low-brightness scene.
When the electronic equipment determines that the low-brightness ratio of the first image is greater than or equal to a first low threshold, the medium-brightness ratio of the first image is greater than or equal to a second low threshold, the high-brightness ratio is less than a third low threshold, and the average pixel brightness of the first image is greater than or equal to a preset low-average brightness, the image type corresponding to the first image is determined to be the image type of the low-medium brightness scene.
When the electronic device determines that the low-brightness ratio of the first image is smaller than a first low threshold, the medium-brightness ratio of the first image is larger than or equal to a second high threshold, the high-brightness ratio is smaller than a third low threshold, the average pixel brightness of the first image is larger than or equal to a preset low average brightness, and the average pixel brightness of the first image is smaller than a preset high average brightness, it is determined that the image type corresponding to the first image is the image type of the medium-brightness scene.
When the electronic device determines that the low-brightness ratio of the first image is smaller than a first low threshold, the medium-brightness ratio of the first image is larger than or equal to a second high threshold, the high-brightness ratio is larger than or equal to a third low threshold, the average pixel brightness of the first image is larger than or equal to a preset low average brightness, and the average pixel brightness of the first image is smaller than a preset high average brightness, it is determined that the image type corresponding to the first image is the image type of the medium-high brightness scene.
When the electronic device determines that the low-brightness ratio of the first image is smaller than a first low threshold, the medium-brightness ratio of the first image is smaller than a second low threshold, the high-brightness ratio is larger than or equal to a third high threshold, and the average pixel brightness of the first image is larger than or equal to a preset high average brightness, it is determined that the image type corresponding to the first image is the image type of the high-brightness scene.
When the electronic device determines that the low-brightness ratio of the first image is greater than or equal to a first low threshold, the medium-brightness ratio of the first image is smaller than a second low threshold, the high-brightness ratio is greater than or equal to a third low threshold, the average pixel brightness of the first image is greater than or equal to a preset low average brightness, and the average pixel brightness of the first image is smaller than a preset high average brightness, it is determined that the image type corresponding to the first image is the image type of the low-high brightness scene.
When the electronic device determines that the low-brightness ratio of the first image is greater than or equal to a first low threshold, the medium-brightness ratio of the first image is greater than or equal to a second low threshold, the high-brightness ratio is greater than or equal to a third low threshold, the average pixel brightness of the first image is greater than or equal to a preset low average brightness, and the average pixel brightness of the first image is less than a preset high average brightness, it is determined that the image type corresponding to the first image is the image type of the uniform-brightness scene.
It should be noted that, in practical applications, other image types may also be determined according to the foregoing manner, and the above-mentioned image types are only part of the embodiments provided in this application and are not to be considered as limitations of this application.
208. And determining a target adjustment type corresponding to the first image according to the image type.
In some embodiments, multiple adjustment types may be preset in the electronic device, and the brightness adjustment manner of the first image corresponding to each adjustment type is different.
The electronic device may set a first preset mapping relationship between the image type and the adjustment type, and after the electronic device determines the image type of the first image, the electronic device may determine the target adjustment type corresponding to the first image directly according to the first preset mapping relationship.
209. And determining the type of the adjusting curve corresponding to the first image according to the target adjusting type.
In some embodiments, the electronic device may preset a database, where a second preset mapping relationship between a plurality of target adjustment types and a plurality of adjustment curve types is stored in the database, and after the electronic device determines the target adjustment type of the first image, the electronic device may determine, according to the second preset mapping relationship, the adjustment curve type corresponding to the first image in the database.
In some embodiments, after acquiring the target adjustment type of the first image, the electronic device may input the target adjustment type into the neural network model, and select a corresponding adjustment curve type through the neural network model.
When the electronic equipment adjusts the brightness curve of the historical image, the corresponding adjusting curve type and the target adjusting type during adjustment are recorded, and then the adjusting curve type and the target adjusting type are input into the initial neural network model for training, so that the neural network model is obtained.
210. And adjusting the brightness value of each pixel of the first image according to the adjustment curve type to obtain a second image.
For example, after determining the image type corresponding to the first image and the adjustment curve type corresponding to the image type, at least a portion of the brightness curve of the first image may be adjusted according to the adjustment curve type.
For example, when the image type is an image type of a low-high brightness scene, the brightness of the high brightness area of the first image can be adaptively reserved without processing, and the brightness of the dark area is reduced to highlight the image details of the dark area, so that the contrast of the first image is improved, and the dark details in the first image are also reserved.
For another example, if the image type is an image type of a medium-brightness scene, it indicates that most of the brightness values of the first image are distributed in the medium-brightness region, and for this case, an S-shaped curve may be selected to improve the dynamic range of the medium-brightness picture and improve the contrast of most of the region in the first image.
Specifically, when the adjustment curve type is an S-shaped curve, the S-shaped curve includes three coordinate points of (0,0), (APL ), and (255 ). Where (0,0) is the origin, (APL ) is a point on the curve, and (255 ) is the vertex of the S-shaped curve.
Assume that there are dark (a, b) and light (c, d) spots on the adjusted curve on the first image. The specific coordinates of the dark area points (a, b) and the bright area points (c, d) can be calculated in the following manner.
First, the low luminance ratio X and the high luminance ratio Y are obtained, and then a can be calculated in a manner of a ═ 20+ (25-X100) × 1.6. The calculation method of b may be calculated by (0.8 × X +0.5) × a.
The calculation method of c can be calculated by the method of c-Y267 +200, and the calculation method of d can be calculated by the method of d-255- (255-c) (0.005 c-0.5).
And finally, determining the brightness curve adjusted to the original brightness curve of the first image by adopting a curve fitting method through the calculated coordinates (a, b) and (c, d) and the coordinates (0,0), (APL ) and (255 ), thereby obtaining a final second image.
It should be noted that, the above is only the image type of the medium-luminance scene, an S-shaped curve of the first image is obtained, and then the luminance curve of the first image is adjusted, so as to obtain an adjusted luminance curve, and finally obtain the second image, where the second image has the luminance characteristics of the adjusted luminance curve. For the first image of other image types, the first image may be adjusted by using other curve adjustment types, so as to obtain the second image.
In some implementations, the electronic device can convert the color space of the second image to an RGB color space to obtain the target image. In practical applications, the image processing method can adjust static images, such as photos. Dynamic images, such as video, may also be adjusted. Through the adjusting mode, each frame of image in the video has good contrast and picture details, so that the picture quality of the whole video is improved, and the impression of a user is improved.
In the embodiment of the present application, the electronic device obtains the number of pixels in the first image and the luminance value corresponding to each pixel in the first image, determines the average pixel luminance according to the number of pixels in the first image and the luminance value corresponding to each pixel, generates the histogram according to the luminance value of each pixel, and performs normalization processing on the histogram to obtain the normalized histogram.
And then determining the low-brightness ratio, the medium-brightness ratio and the high-brightness ratio of the pixels in the first image according to the normalized histogram. And then determining a first high threshold and a first low threshold corresponding to the low brightness ratio, a second high threshold and a second low threshold corresponding to the medium brightness ratio, and a third high threshold and a third low threshold corresponding to the high brightness ratio. And determining the image type corresponding to the first image according to the first high threshold and the first low threshold, the second high threshold and the second low threshold, the third high threshold and the third low threshold and the average pixel brightness. And finally, determining an adjusting curve type corresponding to the first image according to the target adjusting type, and adjusting the brightness value of each pixel of the first image according to the adjusting curve type to obtain a second image. The second image has a better image quality than the first image.
Referring to fig. 3, fig. 3 is a schematic diagram of a first structure of an image processing apparatus according to an embodiment of the present disclosure, where the image processing apparatus may include:
the obtaining module 310 is configured to obtain a first image, and determine a histogram and an average pixel brightness corresponding to the first image.
A first determining module 320, configured to determine an image type corresponding to the first image according to the histogram and the average pixel brightness.
And a second determining module 330, configured to determine, according to the image type, a target adjustment type corresponding to the first image.
The adjusting module 340 is configured to adjust a brightness value of each pixel of the first image according to the target adjustment type to obtain a second image.
In some embodiments, the obtaining module 310 is configured to obtain a luminance value corresponding to each pixel in the first image; and generating the histogram according to the brightness value of each pixel.
In some embodiments, the obtaining module 310 is configured to obtain the number of pixels in the first image and the luminance value corresponding to each pixel in the first image; and determining the average pixel brightness according to the number of pixels in the first image and the brightness value corresponding to each pixel.
In some embodiments, the first determining module 320 is further configured to perform a normalization process on the histogram to obtain a normalized histogram; and determining the image type corresponding to the first image according to the normalized histogram and the average pixel brightness.
In some embodiments, the first determining module 320 is specifically configured to determine a low luminance ratio, a medium luminance ratio, and a high luminance ratio of the pixels in the first image according to the normalized histogram; and determining the image type corresponding to the first image according to the low-brightness ratio, the medium-brightness ratio, the high-brightness ratio and the average pixel brightness.
In some embodiments, the first determining module 320 is specifically configured to determine a first high threshold and a first low threshold corresponding to the low luminance duty ratio, a second high threshold and a second low threshold corresponding to the medium luminance duty ratio, and a third high threshold and a third low threshold corresponding to the high luminance duty ratio; and determining the image type corresponding to the first image according to the first high threshold and the first low threshold, the second high threshold and the second low threshold, the third high threshold and the third low threshold and the average pixel brightness.
In some embodiments, the adjustment module 340 is further configured to determine an adjustment curve type corresponding to the first image according to the target adjustment type; and adjusting the brightness value of each pixel of the first image according to the type of the adjusting curve to obtain the second image.
In some embodiments, the adjusting module 340 is further configured to determine a brightness lookup table corresponding to the first image according to the target adjustment type; determining a mapping brightness value corresponding to each pixel in the first image according to the brightness lookup table; adjusting the brightness value of each pixel to the corresponding mapped brightness value to generate the second image.
Referring to fig. 4, fig. 4 is a schematic diagram of a second structure of an image processing apparatus according to an embodiment of the present application, where the image processing apparatus further includes:
the first conversion module 350 is configured to obtain an initial image, and convert a color space of the initial image into a YUV color space to obtain the first image.
The second conversion module 360 is configured to convert the color space of the second image into an RGB color space to obtain a target image.
In the embodiment of the application, the electronic equipment acquires a first image, determines a histogram and average pixel brightness corresponding to the first image, and then determines an image type corresponding to the first image according to the histogram and the average pixel brightness; determining a target adjustment type corresponding to the first image according to the image type; and finally, adjusting the brightness value of each pixel of the first image according to the target adjustment type to obtain a second image. Due to the fact that the image type corresponding to the first image is determined in the application, the image can be better adjusted by adopting the adjusting type corresponding to the image type, and therefore the image quality of the image is improved.
Accordingly, embodiments of the present application also provide an electronic device, as shown in fig. 5, which may include an input unit 401, a display unit 402, a memory 403 including one or more computer-readable storage media, a sensor 405, a processor 404 including one or more processing cores, and a power supply 406. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 5 does not constitute a limitation of the electronic device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components. Wherein:
the input unit 401 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control. Specifically, in one particular embodiment, input unit 401 may include a touch-sensitive surface as well as other input devices. The touch-sensitive surface, also referred to as a touch display screen or a touch pad, may collect touch operations by a user (e.g., operations by a user on or near the touch-sensitive surface using a finger, a stylus, or any other suitable object or attachment) thereon or nearby, and drive the corresponding connection device according to a predetermined program. Alternatively, the touch sensitive surface may comprise two parts, a touch detection means and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 404, and can receive and execute commands sent by the processor 404. In addition, touch sensitive surfaces may be implemented using various types of resistive, capacitive, infrared, and surface acoustic waves. The input unit 401 may include other input devices in addition to the touch-sensitive surface. In particular, other input devices may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, a joystick, and the like.
The display unit 402 may be used to display information input by or provided to a user and various graphical user interfaces of the electronic device, which may be made up of graphics, text, icons, video, and any combination thereof. The Display unit 402 may include a Display panel, and optionally, the Display panel may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like. Further, the touch-sensitive surface may overlay the display panel, and when a touch operation is detected on or near the touch-sensitive surface, the touch operation is transmitted to the processor 404 to determine the type of touch event, and then the processor 404 provides a corresponding visual output on the display panel according to the type of touch event. Although in FIG. 5 the touch-sensitive surface and the display panel are two separate components to implement input and output functions, in some embodiments the touch-sensitive surface may be integrated with the display panel to implement input and output functions.
The memory 403 may be used for storing software programs and modules, and the processor 404 executes various functional applications and data processing by operating the software programs and modules stored in the memory 403. The memory 403 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the electronic device, and the like. Further, the memory 403 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 403 may also include a memory controller to provide the processor 404 and the input unit 401 access to the memory 403.
The electronic device may also include at least one sensor 405, such as a light sensor, motion sensor, and other sensors. In particular, the light sensor may include an ambient light sensor that may adjust the brightness of the display panel according to the brightness of ambient light, and a proximity sensor that may turn off the display panel and/or the backlight when the electronic device is moved to the ear. As one of the motion sensors, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (generally, three axes), detect the magnitude and direction of gravity when the motion sensor is stationary, and can be used for applications (such as horizontal and vertical screen switching, related games, magnetometer attitude calibration) for recognizing the attitude of an electronic device, vibration recognition related functions (such as pedometer and tapping), and the like; as for other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which may be further configured to the electronic device, detailed descriptions thereof are omitted.
The processor 404 is a control center of the electronic device, connects various parts of the whole electronic device by various interfaces and lines, performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in the memory 403 and calling data stored in the memory 403, thereby performing overall monitoring of the electronic device. Optionally, processor 404 may include one or more processing cores; preferably, the processor 404 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 404.
The electronic device also includes a power supply 406 (e.g., a battery) for powering the various components, which may preferably be logically coupled to the processor 404 via a power management system to manage charging, discharging, and power consumption management functions via the power management system. The power supply 406 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.
Although not shown, the electronic device may further include a camera, a bluetooth module, and the like, which are not described in detail herein. Specifically, in this embodiment, the processor 404 in the electronic device loads the executable file corresponding to the process of one or more application programs into the memory 403 according to the following instructions, and the processor 404 runs the application programs stored in the memory 403, so as to implement various functions:
acquiring a first image, and determining a histogram and average pixel brightness corresponding to the first image;
determining the image type corresponding to the first image according to the histogram and the average pixel brightness;
determining a target adjustment type corresponding to the first image according to the image type;
and adjusting the brightness value of each pixel of the first image according to the target adjustment type to obtain a second image.
It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.
To this end, the present application provides a computer-readable storage medium, in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any one of the image processing methods provided by the embodiments of the present application. For example, the instructions may perform the steps of:
acquiring a first image, and determining a histogram and average pixel brightness corresponding to the first image;
determining the image type corresponding to the first image according to the histogram and the average pixel brightness;
determining a target adjustment type corresponding to the first image according to the image type;
and adjusting the brightness value of each pixel of the first image according to the target adjustment type to obtain a second image.
The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.
Wherein the computer-readable storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
Since the instructions stored in the storage medium can execute the steps in any image processing method provided in the embodiments of the present application, beneficial effects that can be achieved by any image processing method provided in the embodiments of the present application can be achieved, which are detailed in the foregoing embodiments and will not be described herein again.
The foregoing detailed description has provided an image processing method, an image processing apparatus, an electronic device, and a storage medium according to embodiments of the present application, and specific examples have been applied in the present application to explain the principles and implementations of the present application, and the descriptions of the foregoing embodiments are only used to help understand the method and the core ideas of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims (14)

1. An image processing method, comprising:
acquiring a first image, and determining a histogram and average pixel brightness corresponding to the first image;
determining the image type corresponding to the first image according to the histogram and the average pixel brightness;
determining a target adjustment type corresponding to the first image according to the image type;
and adjusting the brightness value of each pixel of the first image according to the target adjustment type to obtain a second image.
2. The method according to claim 1, wherein the step of determining the image type corresponding to the first image according to the histogram and the average pixel luminance comprises:
carrying out normalization processing on the histogram to obtain a normalized histogram;
and determining the image type corresponding to the first image according to the normalized histogram and the average pixel brightness.
3. The method according to claim 2, wherein the step of determining the image type corresponding to the first image according to the normalized histogram and the average pixel luminance comprises:
determining a low-brightness ratio, a medium-brightness ratio and a high-brightness ratio of pixels in the first image according to the normalized histogram;
and determining the image type corresponding to the first image according to the low-brightness ratio, the medium-brightness ratio, the high-brightness ratio and the average pixel brightness.
4. The image processing method according to claim 3, wherein the step of determining the low-luminance ratio, the medium-luminance ratio, and the high-luminance ratio corresponding to the first image according to the normalized histogram includes:
determining a low brightness threshold value and a high brightness threshold value corresponding to the normalized histogram;
and determining the low brightness ratio, the medium brightness ratio and the high brightness ratio according to the low brightness threshold and the high brightness threshold.
5. The method according to claim 3, wherein the step of determining the image type corresponding to the first image according to the low luminance ratio, the medium luminance ratio, the high luminance ratio, and the average pixel luminance comprises:
determining a first high threshold and a first low threshold corresponding to the low brightness ratio, a second high threshold and a second low threshold corresponding to the medium brightness ratio, and a third high threshold and a third low threshold corresponding to the high brightness ratio;
and determining the image type corresponding to the first image according to the first high threshold and the first low threshold, the second high threshold and the second low threshold, the third high threshold and the third low threshold and the average pixel brightness.
6. The method according to claim 1, wherein the step of adjusting the brightness value of each pixel of the first image according to the target adjustment type to obtain a second image comprises:
determining the type of an adjusting curve corresponding to the first image according to the target adjusting type;
and adjusting the brightness value of each pixel of the first image according to the type of the adjusting curve to obtain the second image.
7. The method according to claim 1, wherein the step of adjusting the brightness value of each pixel of the first image according to the target adjustment type to obtain a second image comprises:
determining a brightness lookup table corresponding to the first image according to the target adjustment type;
determining a mapping brightness value corresponding to each pixel in the first image according to the brightness lookup table;
adjusting the brightness value of each pixel to the corresponding mapped brightness value to generate the second image.
8. The image processing method according to any one of claims 1 to 7, wherein, prior to the step of acquiring the first image, the method further comprises:
obtaining an initial image, and converting the color space of the initial image into a YUV color space to obtain the first image.
9. The image processing method according to any one of claims 1 to 7, wherein the step of determining the histogram corresponding to the first image comprises:
acquiring a brightness value corresponding to each pixel in the first image;
and generating the histogram according to the brightness value of each pixel.
10. The method according to any of claims 1-7, wherein said step of determining an average pixel intensity corresponding to said first image comprises:
acquiring the number of pixels in the first image and a brightness value corresponding to each pixel in the first image;
and determining the average pixel brightness according to the number of pixels in the first image and the brightness value corresponding to each pixel.
11. The method according to any of claims 1-7, wherein after said step of adjusting a brightness value of each pixel of said first image according to said target adjustment type to obtain a second image, said method further comprises:
and converting the color space of the second image into an RGB color space to obtain a target image.
12. An image processing apparatus characterized by comprising:
the device comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring a first image and determining a histogram and average pixel brightness corresponding to the first image;
the first determining module is used for determining the image type corresponding to the first image according to the histogram and the average pixel brightness;
the second determining module is used for determining a target adjusting type corresponding to the first image according to the image type;
and the adjusting module is used for adjusting the brightness value of each pixel of the first image according to the target adjusting type to obtain a second image.
13. An electronic device, comprising:
a memory storing executable program code, a processor coupled with the memory;
the processor calls the executable program code stored in the memory to perform the steps in the image processing method according to any one of claims 1 to 11.
14. A computer-readable storage medium storing a plurality of instructions adapted to be loaded by a processor to perform the steps of the image processing method according to any one of claims 1 to 11.
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