WO2022116989A1

WO2022116989A1 - Image processing method and apparatus, and device and storage medium

Info

Publication number: WO2022116989A1
Application number: PCT/CN2021/134713
Authority: WO
Inventors: 苏坦
Original assignee: 影石创新科技股份有限公司
Priority date: 2020-12-01
Filing date: 2021-12-01
Publication date: 2022-06-09
Also published as: CN112565636B; CN112565636A

Abstract

The present application relates to an image processing method and apparatus, and a computer device and a storage medium. The method comprises: acquiring a first dynamic image to be processed; acquiring an image brightness statistical value corresponding to the first dynamic image; acquiring an ambient illumination intensity statistical value, and acquiring, according to the ambient illumination intensity statistical value, a target brightness statistical value corresponding to a photographing environment; determining a target brightness correction coefficient according to the target brightness statistical value and the image brightness statistical value; performing brightness correction on the first dynamic image according to the target brightness correction coefficient, so as to obtain a target brightness correction image; and performing pixel dynamic range mapping on the target brightness correction image, so as to obtain a target dynamic image, wherein the pixel dynamic range of the target dynamic image is smaller than the pixel dynamic range of the first dynamic image. By means of the present method, the effect of image processing can be improved.

Description

Image processing method, apparatus, device and storage medium

technical field

The present application relates to the technical field of image processing, and in particular, to an image processing method, apparatus, device and storage medium.

Background technique

With the development of image processing technology, high dynamic images are widely used because they can provide more dynamic range and image details. However, in some applications, the dynamic range of the display device that often needs to display images is limited dynamic range or low dynamic range, and low dynamic range is relative to high dynamic range, for example, CRT (Cathode Ray Tube) display, LCD display or Projectors, etc., have limited dynamic range. There are often situations in which high dynamic range images need to be displayed on the above-mentioned limited dynamic range devices. In this case, the high dynamic Displays the same effect as HDR on display devices with limited dynamic range.

technical problem

However, in the current image processing method, when converting a high dynamic image into a low dynamic image, there are problems that the image details are lost more and the image processing effect is poor.

technical solutions

Based on this, it is necessary to provide an image processing method, apparatus, computer equipment and storage medium that retain more image details and improve image processing effects when converting a high dynamic image into a low dynamic image.

In a first aspect, the present invention provides an image processing method, the method comprising:

obtaining the first dynamic image to be processed;

obtaining the image brightness statistics value corresponding to the first dynamic image;

Obtaining a statistical value of ambient light intensity, and obtaining a statistical value of target brightness corresponding to the shooting environment according to the statistical value of ambient light intensity; the statistical value of ambient light intensity is a statistical value of light intensity of the shooting environment where the first dynamic image is located;

Determine a target brightness correction coefficient according to the target brightness statistic value and the image brightness statistic value;

Perform brightness correction on the first dynamic image according to the target brightness correction coefficient to obtain a target brightness correction image;

Performing pixel dynamic range mapping on the target brightness correction image to obtain a target dynamic image, wherein the pixel dynamic range of the target dynamic image is smaller than the pixel dynamic range of the first dynamic image.

In one embodiment, the determining of the target brightness correction coefficient according to the target brightness statistic value and the image brightness statistic value includes at least one of the following steps:

When the target brightness statistic value is greater than the image brightness statistic value, obtain a brightness enhancement coefficient as a target brightness correction coefficient;

When the target brightness statistic value is smaller than the image brightness statistic value, a brightness reduction coefficient is obtained.

In one embodiment, the target brightness correction coefficient includes a first brightness correction coefficient, and the determining the target brightness correction coefficient according to the target brightness statistics value and the image brightness statistics value includes:

Calculate the brightness ratio of the target brightness statistic value and the image brightness statistic value;

Taking the luminance ratio as a true number in a logarithmic function, logarithm calculation is performed to obtain a first luminance correction coefficient, wherein the base of the logarithmic function is greater than 1.

In one embodiment, the target brightness correction coefficient further includes a second brightness correction coefficient and a third brightness correction coefficient; the target brightness correction coefficient is determined according to the target brightness statistics value and the image brightness statistics value:

performing a reduction process on the first brightness correction coefficient to obtain a second brightness correction coefficient;

performing increasing processing on the first brightness correction coefficient to obtain a third brightness correction coefficient;

The performing brightness correction on the first dynamic image according to the target brightness correction coefficient to obtain a target brightness correction image includes:

Performing brightness correction on the first dynamic image according to the first brightness correction coefficient, the second brightness correction coefficient, and the third brightness correction coefficient, respectively, to obtain a first brightness corrected by the first brightness correction coefficient a corrected image, a second brightness corrected image corrected by the second brightness correction coefficient, and a third brightness corrected image corrected by the third brightness correction coefficient;

The performing pixel dynamic range mapping on the target brightness correction image to obtain the target dynamic image includes:

Perform pixel dynamic range mapping on the first brightness-corrected image, the second brightness-corrected image, and the third brightness-corrected image, respectively, to obtain a first mapped dynamic image corresponding to the first brightness-corrected image, the The second mapping dynamic image corresponding to the two brightness correction images and the third mapping dynamic image corresponding to the third brightness correction image;

Fusion processing is performed on the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image to obtain a target dynamic image.

In one of the embodiments, the described first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image are fused to obtain the target dynamic image including:

Perform fusion processing on the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image to obtain a fusion processed image;

obtaining the image area of the fusion processing image;

Get the reference image area;

Calculate the local mapping gain value of the image area of the fused image relative to the reference image area;

Tone-mapping processing is performed on the first dynamic image according to the local mapping gain value to obtain a target dynamic image.

In one of the embodiments, the obtaining a statistical value of the ambient light intensity includes:

acquiring the sensitivity, shutter speed and aperture value corresponding to the first dynamic image;

Obtain the first parameter value according to the sensitivity, shutter speed and aperture value;

calculating the parameter ratio of the image brightness statistic to the first parameter;

The parameter ratio is used as the true number of the logarithmic function to perform logarithmic calculation to obtain a statistical value of the ambient light intensity, wherein the base of the logarithmic function is greater than 1.

In a second aspect, the present invention provides an image processing device, the device comprising:

a first dynamic image acquisition module, configured to acquire the first dynamic image to be processed;

an image brightness statistical value acquisition module, configured to acquire an image brightness statistical value corresponding to the first dynamic image;

a target brightness statistical value acquisition module, configured to acquire a statistical value of ambient light intensity, and obtain a statistical value of target brightness corresponding to the shooting environment according to the statistical value of ambient light intensity;

a target brightness correction coefficient determination module, configured to determine a target brightness correction coefficient according to the target brightness statistic value and the image brightness statistic value;

a target brightness correction image determination module, configured to perform brightness correction on the first dynamic image according to the target brightness correction coefficient to obtain a target brightness correction image;

The target dynamic image determination module is used for performing pixel dynamic range mapping on the target brightness correction image to obtain the target dynamic image.

In one embodiment, the target brightness correction coefficient determination module includes at least one of the following units:

a brightness enhancement coefficient obtaining unit, configured to obtain a brightness enhancement coefficient as a target brightness correction coefficient when the target brightness statistic value is greater than the image brightness statistic value;

A brightness reduction coefficient obtaining unit, configured to obtain a brightness reduction coefficient as a target brightness correction coefficient when the target brightness statistic value is less than the image brightness statistic value.

In a third aspect, the present invention provides a computer device, comprising a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

obtaining the first dynamic image to be processed;

In a fourth aspect, the present invention provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

obtaining the first dynamic image to be processed;

beneficial effect

In the above image processing method, device, computer equipment and storage medium, by acquiring the first dynamic image to be processed, the image brightness statistical value of the first dynamic image is acquired; by acquiring the ambient light intensity statistical value, according to the ambient light intensity statistical value Obtain the target brightness statistics value corresponding to the shooting environment, determine the target brightness correction coefficient according to the target brightness statistics value and the image brightness statistics value, and perform brightness correction on the first dynamic image through the target brightness correction coefficient to obtain the target brightness correction image. The correction coefficient of the image can be determined according to the ambient light intensity, and the brightness of the first dynamic image can be corrected by using the correction coefficient, so that an image with suitable brightness and more details can be obtained. The target dynamic image is obtained by performing pixel dynamic range mapping on the target brightness correction image, wherein the pixel dynamic range of the target dynamic image is smaller than the pixel dynamic range of the first dynamic image, thereby realizing the conversion from a high dynamic image to a low dynamic image. Through the above process, it is realized that the image correction coefficient is determined by the ambient light intensity and the statistical value of the image brightness when the image is taken, and the image is corrected by the image correction coefficient, so that the brightness of the corrected image can be matched with the shooting environment. On the basis of appropriate brightness, when a high dynamic image is processed into a low dynamic image, more image details can be preserved and the image processing effect can be improved.

Description of drawings

Fig. 1 is the application environment diagram of the image processing method in one embodiment;

2 is a schematic flowchart of an image processing method in one embodiment;

3 is a schematic flowchart of a step of determining a target brightness correction coefficient according to a target brightness statistic value and an image brightness statistic value in another embodiment;

4 is a schematic flowchart of a method for obtaining a target dynamic image by performing fusion processing on a first mapping dynamic image, a second mapping dynamic image, and a third mapping dynamic image in another embodiment;

5 is a schematic flowchart of obtaining a statistical value of ambient light intensity in another embodiment;

6 is a schematic diagram of a normal image in one embodiment;

7 is a schematic diagram of a darker image in one embodiment;

8 is a schematic diagram of a brighter image in one embodiment;

9 is a structural block diagram of an image processing apparatus in one embodiment;

Figure 10 is a diagram of the internal structure of a computer device in one embodiment.

Embodiments of the present invention

In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

The image processing method provided in this application can be applied to the application environment shown in FIG. 1 . The application environment includes an image capturing device 102 and a terminal 104 , wherein the image capturing device 102 and the terminal 104 are connected in communication. After the image acquisition device 102 collects the dynamic image, it transmits it to the terminal 104. The terminal 104 acquires the first dynamic image to be processed, and the terminal 104 can acquire the image brightness statistics value and the environment corresponding to the first dynamic image through the acquired first dynamic image. The statistical value of light intensity, according to the statistical value of ambient light intensity, the statistical value of target brightness corresponding to the shooting environment is obtained; wherein, the statistical value of ambient light intensity is the statistical value of light intensity of the shooting environment where the first dynamic image is located; the terminal 104 is based on the statistical value of target brightness and the statistical value of light intensity of the shooting environment. The image brightness statistics value determines the target brightness correction coefficient; performs brightness correction on the first dynamic image according to the target brightness correction coefficient to obtain the target brightness correction image; performs pixel dynamic range mapping on the target brightness correction image to obtain the target dynamic image. The pixel dynamic range of the target dynamic image is smaller than the pixel dynamic range of the first dynamic image. The image capturing device 102 may be, but is not limited to, various devices having an image capturing function, and may be distributed outside the terminal 104 or inside the terminal 104 . For example: various cameras, scanners, various cameras, and image capture cards distributed outside the terminal 104 . The terminal 104 may be, but is not limited to, various cameras, personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices.

It can be understood that the method provided by the embodiment of the present application may also be executed by a server.

In one embodiment, as shown in FIG. 2, an image processing method is provided, and the method is applied to the terminal in FIG. 1 as an example for description, including the following steps:

Step 202, acquiring the first dynamic image to be processed.

The dynamic image refers to a dynamic range image, and the dynamic range image refers to an image whose brightness is within a certain range. Dynamic range images are classified into high dynamic range images (High-Dynamic Range, HDR), low dynamic range images or limited dynamic range images.

Specifically, after the terminal receives the image processing instruction, the image processing instruction carries the image identifier of the image to be processed, and through the image identifier, the terminal can obtain the first dynamic image to be processed from the stored image. The terminal acquires the first dynamic image to be processed so as to perform subsequent processing work on the first dynamic image.

In one embodiment, the first dynamic image may be acquired by a acquisition device having a dynamic range image acquisition function.

In one embodiment, the terminal may be an image to be displayed, and as the first dynamic image to be processed, the terminal may directly perform image processing on the displayed image.

In one embodiment, the first dynamic image may be obtained by synthesizing images with different exposures. Images with different exposures have different brightness. Appropriate exposure will make the image have appropriate brightness and more image details. Images with too low exposure or too high exposure will lose image details.

Step 204: Acquire a statistical value of image brightness corresponding to the first dynamic image.

Among them, the statistical value of image brightness refers to the comprehensive quantitative performance of image brightness, and the overall situation of image brightness can be obtained from the statistical value of image brightness.

Specifically, after acquiring the first dynamic image, the terminal obtains a brightness histogram by converting the first dynamic image into a grayscale image and statistics. to the average brightness of the first moving image.

Step 206: Obtain a statistical value of ambient light intensity, and obtain a statistical value of target brightness corresponding to the shooting environment according to the statistical value of ambient light intensity; the statistical value of ambient light intensity is a statistical value of light intensity of the shooting environment where the first dynamic image is located.

Among them, the statistical value of the ambient light intensity refers to the comprehensive quantitative performance of the ambient light intensity. The overall situation of the ambient light intensity can be known through the statistical value of the ambient light intensity. The statistical value is obtained through statistics, such as the average or the median. .

Specifically, after acquiring the statistical value of image brightness and the statistical value of ambient light intensity corresponding to the first dynamic image, the terminal can obtain the corresponding value of the statistical value of ambient light intensity according to the corresponding relationship between the statistical value of ambient light intensity and the statistical value of target brightness. target brightness statistics.

In one embodiment, the exposure parameter can be obtained according to the sensitivity, shutter speed and aperture value, and the statistical value of the image brightness is divided by the exposure parameter as the true number of the logarithmic function, and the logarithmic calculation is performed to obtain the statistical value of the ambient light intensity. The statistical value of ambient light intensity is expressed as EE, the statistical value of image brightness is expressed as V0, the statistical value of target brightness is expressed as V, I is the sensitivity, s is the shutter speed in seconds, a is the aperture value, and the statistical value of ambient light intensity is related to the image. The relationship between the luminance statistics can be expressed as:

EE=log ₂ (V0/(I*s/a ² )

Different statistical values of ambient light intensity have different statistical values of target brightness. Assuming that the statistical value of target brightness is V, there is a one-to-one correspondence between the statistical value of ambient light intensity EE and the statistical value of target brightness V. It is understandable that images taken under different ambient light intensities have different image brightness that the user likes. For example, for photos taken in sunny days with sufficient light, people prefer brighter pictures, so the target brightness statistic value V corresponding to the ambient light intensity statistic value EE is too large, and for images taken outdoors at night, the appropriate brightness The target brightness statistic value V corresponding to the ambient light intensity statistic value EE of the image is relatively small.

In one embodiment, there is a one-to-one correspondence between the statistical value of ambient light intensity EE and the statistical value of target brightness V, which may be denoted as f. For example, assuming that the brightness value of an image pixel is between 0 and 1, f can be a mapping table, as shown in Table 1, which is part of the data in the mapping table f:

EE(cd/m ²) EE(cd/m ² )	-12-12	-10-10	-8-8	-4-4	-2-2	33	55
V(cd/m ²) V(cd/m ² )	0.0250.025	0.050.05	0.20.2	0.250.25	0.3750.375	0.50.5	0.50.5

Table 1 The mapping table between the statistical value of ambient light intensity and the statistical value of target brightness

From Table 1, the numerical relationship between different ambient light intensity statistics EE and the corresponding target brightness statistics V can be obtained, and the numerical relationship is unique. Based on this one-to-one correspondence, the target brightness statistic V can be expressed as f(EE), and the target brightness statistic f(EE) under a certain illumination intensity can be adjusted by adjusting the value in this correspondence, so that the Images can be made lighter or darker.

Step 208: Determine the target brightness correction coefficient according to the target brightness statistic value and the image brightness statistic value.

The brightness correction coefficient is a coefficient for performing brightness correction on the image. The image can be adjusted to the appropriate brightness through the brightness correction coefficient, such as brightening or darkening.

Specifically, after the terminal has obtained the statistical value of target brightness and the statistical value of image brightness, through the functional relationship between the statistical value of target brightness and the statistical value of image brightness, for example, there is a ratio between the statistical value of target brightness and the statistical value of image brightness The type of functional relationship can determine the target brightness correction coefficient.

In one embodiment, the statistical value of target brightness is expressed as f(EE), the statistical value of image brightness is expressed as V0, and the target brightness correction is obtained through the functional relationship between the target brightness correction coefficient, the target brightness statistical value and the image brightness statistical value. coefficient. For example, the target luminance correction coefficient is β, and β can be expressed as: β=log ₂ (f(EE)/V ₀ )

Step 210: Perform brightness correction on the first dynamic image according to the target brightness correction coefficient to obtain a target brightness corrected image.

Specifically, the terminal performs brightness correction on the first dynamic image according to the determined target brightness correction coefficient, and acquires the corrected first dynamic image as the target brightness correction image. For example, a pixel value after brightness correction can be obtained by multiplying each pixel value of the first dynamic image by a target brightness correction coefficient, and an image composed of the corrected pixel values is a target brightness correction image.

In one embodiment, the brightness correction of the first dynamic image may be performed directly by using the target brightness correction coefficient, so that the image brightness statistical value of the corrected first dynamic image is close to the target brightness statistical value. For example, assuming that the value of each pixel in the first dynamic image is X, and using the target brightness correction coefficient e1 to correct the brightness of the first dynamic image, the obtained pixel value of the corresponding position of the target brightness corrected image is X*e1; A final correction coefficient is obtained by calculating a function having a corresponding relationship with the target brightness correction coefficient, and brightness correction is performed on the first moving image by using the final correction coefficient. For example, the function related to the target brightness correction coefficient is an exponential function, the brightness correction coefficient can be used as an exponent, and the preset value is used as the base to perform exponential calculation, and the preset value is a number greater than 1. For example, assuming that the preset value is 2, the final obtained correction coefficient is 2 ^e1 , and the obtained pixel value of the corresponding position of the target brightness corrected image is X*2 ^e1 .

Step 212: Perform pixel dynamic range mapping on the target brightness correction image to obtain a target dynamic image, where the pixel dynamic range of the target dynamic image is smaller than the pixel dynamic range of the first dynamic image.

Specifically, dynamic range mapping refers to mapping an image from one dynamic range to another dynamic range. The pixel dynamic range of the first dynamic image is larger than the pixel dynamic range of the target dynamic image. In order to adapt the pixel dynamic range of the image to a display device with limited or low dynamics, the target brightness correction image obtained by the terminal needs to be subjected to the pixel dynamic range. Mapping, converts high dynamic images into low dynamic images, so that the mapped images can adapt to low dynamic display devices.

In one embodiment, after the target brightness correction image is obtained by correcting the first dynamic image by using the brightness correction coefficient, the target brightness correction image at this time is still a high dynamic image, which needs to be converted into a low dynamic image by dynamic range mapping images, so that low-motion images can be used as target motion images for low-motion devices.

In one embodiment, the transformation from a high dynamic image to a low dynamic image can be achieved using a gamma transform. For example, converting from a high-motion image with pixel values ranging from 0 to 65535 to a low-motion image with pixel values ranging from 0 to 255.

In the above image processing method, by acquiring the first dynamic image to be processed, the image brightness statistics value of the first dynamic image is acquired; by acquiring the ambient light intensity statistics value, the target brightness corresponding to the shooting environment is acquired according to the ambient light intensity statistics value. Statistical value, the target brightness correction coefficient is determined according to the target brightness statistical value and the image brightness statistical value, and the brightness correction is performed on the first dynamic image through the target brightness correction coefficient to obtain a target brightness correction image. The correction coefficient of the image can be determined according to the ambient light intensity, and the brightness of the first dynamic image can be corrected by using the correction coefficient, so that an image with suitable brightness and more details can be obtained. The target dynamic image is obtained by performing pixel dynamic range mapping on the target brightness correction image, wherein the pixel dynamic range of the target dynamic image is smaller than the pixel dynamic range of the first dynamic image, thereby realizing the conversion from a high dynamic image to a low dynamic image. Through the above process, it is realized that the image correction coefficient is determined by the ambient light intensity and the statistical value of the image brightness when the image is taken, and the image is corrected by the image correction coefficient. To the image processing process of low dynamic images, more image details are preserved and the image processing effect is improved.

In one embodiment, determining the target brightness correction coefficient according to the target brightness statistical value and the image brightness statistical value includes at least one of the following steps: when the target brightness statistical value is greater than the image brightness statistical value, acquiring a brightness enhancement coefficient as the target brightness correction coefficient ; When the target brightness statistic value is less than the image brightness statistic value, obtain the brightness reduction coefficient as the target brightness correction coefficient.

Specifically, the brightness enhancement coefficient enhances the brightness. When the target brightness statistic value is greater than the image brightness statistic value, the target brightness correction coefficient will enhance the brightness of the image. The target brightness correction coefficient at this time may be called a brightness enhancement coefficient. The brightness enhancement coefficient can enhance the image brightness linearly or nonlinearly. The brightness enhancement coefficient and the brightness reduction coefficient may be preset, or may be calculated by a preset algorithm. For example, the brightness ratio between the target brightness statistic and the image brightness statistic can be calculated; the brightness ratio is used as the true number in the logarithmic function to perform logarithmic calculation to obtain the first brightness correction coefficient, where the base of the logarithmic function is greater than 1.

In one embodiment, the target luminance statistic value can be expressed as f(EE), the image luminance statistic value is V0, the target luminance correction coefficient is α, and α can be expressed as: α=2 ^e

Among them, e can be expressed as: e=log ₂ (f(EE)/V ₀ )

When the statistical value of target brightness is greater than the statistical value of image brightness, f(EE)/V0 is a positive number greater than 1, at this time e is a positive number greater than 0, then α is a positive number greater than 1, multiply α by the The pixel value will increase the brightness. At this time, e can be called the brightness enhancement coefficient, and the brightness of the image can be enhanced and adjusted. When the statistical value of target brightness is less than the statistical value of image brightness, f(EE)/V0 is a positive number less than 1, and e is a negative number less than 0, then α is a positive number less than 1, and e can be called brightness Decrease the coefficient to decrease the brightness of the image.

In this embodiment, the purpose of determining the target brightness coefficient can be achieved through the target brightness statistical value and the image brightness statistical value, and the brightness of the image can be enhanced or attenuated by using the target brightness coefficient.

In one embodiment, the target brightness correction coefficient includes a first brightness correction coefficient, and determining the target brightness correction coefficient according to the target brightness statistic value and the image brightness statistic value includes: calculating the brightness ratio of the target brightness statistic value and the image brightness statistic value; The ratio is used as the true number in the logarithmic function to perform logarithmic calculation to obtain the first brightness correction coefficient.

Specifically, the terminal may obtain the first brightness correction coefficient through the statistical value of target brightness and the statistical value of image brightness, for example, firstly calculate the brightness ratio of the statistical value of target brightness to the statistical value of image brightness. For example, the statistical value of target brightness is expressed as f(EE), the statistical value of image brightness is V0, and the calculated ratio is expressed as a, then a can be expressed as: a=f(EE)/V0

The first luminance correction coefficient can be expressed as e1, wherein the base of the logarithmic function is greater than 1. For example, e1 is a logarithmic function with an integer base as the base, and e1 can vary with the change of the true number of the logarithmic function. For example, e1 is a base-2, monotonically increasing logarithmic function, e1=log ₂ a

In this embodiment, if the true number of the logarithmic function is greater than 1, the luminance ratio is positively correlated with the first luminance correction coefficient, and the first luminance correction coefficient is obtained by calculating the luminance ratio between the target luminance statistical value and the image luminance statistical value, such that The brightness ratio reflects the magnitude relationship between the target brightness statistic value and the image brightness statistic value. When the target brightness statistic value is greater than the image brightness statistic value, the first brightness enhancement coefficient is the brightness enhancement coefficient. When the target brightness statistic value is smaller than the image brightness statistic value, the first brightness enhancement coefficient is a brightness reduction coefficient. Therefore, the adjusted image is matched with the ambient brightness where the shooting environment is located.

In one embodiment, as shown in FIG. 3 , the target brightness correction coefficient further includes a second brightness correction coefficient and a third brightness correction coefficient; and determining the target brightness correction coefficient according to the target brightness statistics value and the image brightness statistics value includes:

Step 302 , reducing the first brightness correction coefficient to obtain a second brightness correction coefficient.

Specifically, after the first brightness correction coefficient is obtained, the first brightness correction coefficient may be reduced based on the first brightness correction coefficient, and the second brightness correction coefficient may be obtained.

In one embodiment, reducing the first luminance correction coefficient may be in the form of reducing a corresponding percentage. For example, if the original correction coefficient is b, the second luminance correction coefficient b1=b−0.1b=0.9b obtained after the reduction can be obtained in the form of reducing 0.1b.

In one embodiment, reducing the first luminance correction coefficient may be in the form of reducing the corresponding coefficient value. For example, if the original correction coefficient is b, the second brightness correction coefficient b1=b-m can be obtained by reducing the numerical value m, where m can be any positive number, for example, 3.

Step 304 , performing an increase process on the first brightness correction coefficient to obtain a third brightness correction coefficient.

Specifically, after the first brightness correction coefficient is obtained, the first brightness correction coefficient may be increased based on the first brightness correction coefficient, and the third brightness correction coefficient may be obtained.

In one embodiment, the first luminance correction coefficient may be increased in the form of increasing a corresponding percentage. For example, if the original correction coefficient is b, the third luminance correction coefficient b1=b+0.1b=1.1b obtained after the reduction can be obtained in the form of adding 0.1b.

In one embodiment, the process of increasing the first luminance correction coefficient may be in the form of increasing the corresponding coefficient value. For example, if the original correction coefficient is b, a third brightness correction coefficient b1=b+n can be obtained by increasing the numerical value n, where n is any positive number, for example, 3.

Step 306: Perform brightness correction on the first dynamic image according to the first brightness correction coefficient, the second brightness correction coefficient, and the third brightness correction coefficient, respectively, to obtain a first brightness correction image and a second brightness correction image obtained by modifying the first brightness correction coefficient. The second brightness correction image obtained by the coefficient correction and the third brightness correction image obtained by the third brightness correction coefficient correction.

Specifically, after the terminal acquires the first brightness correction coefficient, the second brightness correction coefficient, and the third brightness correction coefficient, the terminal uses the first brightness correction coefficient, the second brightness correction coefficient, and the third brightness correction coefficient to modify the first dynamic image respectively. After processing, a first brightness corrected image, a second brightness corrected image and a third brightness corrected image are obtained. For example, the first brightness correction coefficient is used as the target correction coefficient, and the corresponding first brightness correction image is used as the target correction image. Since the second brightness correction image is the correction image corresponding to the reduction of the brightness correction coefficient, the second brightness correction is a darker image; similarly, the third brightness corrected image is a brighter image.

In one embodiment, when the first brightness correction coefficient is large, the third brightness correction coefficient can be configured to be closer to the first brightness correction coefficient; when the first brightness correction coefficient is small, the second brightness correction coefficient can be configured to be closer to at the first brightness correction coefficient. Therefore, the details of each brightness level in the picture can be better balanced, so that the image corrected by the correction coefficient can reflect more details of the target image.

Step 308: Perform pixel dynamic range mapping on the first brightness-corrected image, the second brightness-corrected image, and the third brightness-corrected image, respectively, to obtain a first mapped dynamic image corresponding to the first brightness-corrected image, and a first mapped dynamic image corresponding to the second brightness-corrected image. The second mapping dynamic image and the third mapping dynamic image corresponding to the third brightness correction image.

In one embodiment, pixel dynamic range mapping may be performed on the first brightness-corrected image, the second brightness-corrected image, and the third brightness-corrected image by means of gamma transformation, to obtain the first mapping dynamic range corresponding to the first brightness-corrected image. The image, the second mapping dynamic image corresponding to the second brightness correction image, and the third mapping dynamic image corresponding to the third brightness correction image. In this way, a high-dynamic brightness correction image is transformed into a low-dynamic-range mapped dynamic image, and a low-dynamic-range mapped dynamic image with different brightness is obtained.

In one embodiment, the low dynamic range image may be an eight-bit low dynamic range image, the high dynamic correction image may be a sixteen-bit high dynamic range image, the high dynamic range image has three channels of red, green and blue, and the pixel value range is An image between 0 and 65535, a low dynamic range image is an image with three channels of red, green and blue, and the pixel value range is between 0 and 255.

Step 310: Perform fusion processing on the first mapping dynamic image, the second mapping dynamic image, and the third mapping dynamic image to obtain a target dynamic image.

Among them, the fusion processing refers to the fusion of images with different brightness according to a certain image fusion method, so that the processed image has richer image details.

Specifically, first, the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image are down-sampled; according to the down-sampled first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image, obtain the first weight map corresponding to the first mapped dynamic image, the second weight map corresponding to the second mapped dynamic image, and the third weight map corresponding to the third mapped dynamic image; the down-sampled first mapped dynamic image, The second mapping dynamic image and the third mapping dynamic image are converted into grayscale images respectively, and multi-resolution fusion is performed on the three grayscale images and the first weight map, the second weight map and the third weight map to obtain multi-resolution rate fusion grayscale image; according to this grayscale image, and the down-sampled first mapping dynamic image, second mapping dynamic image and third mapping dynamic image are converted into three grayscale images and the first weight map, the third For the second weight map and the third weight map, new weight maps are obtained by the following formulas, which are the fourth weight map, the fifth weight map and the sixth weight map, respectively. Suppose the new weight map is represented as _wi ', the first weight map, the second weight map and the third weight map are represented as w _i , where i∈(1,2,3), multi-resolution fusion The grayscale image is represented as If, and the _grayscale images converted from the first mapping dynamic image, the second mapping dynamic image, and the third mapping dynamic image are respectively represented as I ₁ , I ₂ , and I ₃ , then the new weight map Expressed as w _i ', it can be obtained by the following formula:

w _i '=kw _i

I _f '=w ₁ I ₁ +w ₂ I ₂ +w ₃ I ₃ ,i∈(1,2,3)

After up-sampling the new weight map, the fourth weight map, the fifth weight map and the sixth weight map respectively, it forms the same size as the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image. After weighted fusion of the fourth weight map, the fifth weight map and the sixth weight map with the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image, the final fused target is obtained dynamic images. It can be understood that the above-mentioned image fusion method can use other fusion methods that can achieve the same effect.

In one embodiment, the multi-resolution fusion method can also adopt the multi-resolution fusion method of biorthogonal wavelet transform, which can utilize the redundant and complementary information of multiple images, so that the fused image can contain more abundant and comprehensive information. information.

In one embodiment, the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image may be fused by the Laplacian pyramid weighted fusion method to obtain the target dynamic image.

In this embodiment, the second brightness correction coefficient and the third brightness correction coefficient are respectively obtained by using the first brightness correction coefficient, and the first brightness correction image, the second brightness correction image and the third brightness correction image are obtained by using the above three correction coefficients. image, and obtain the corresponding mapping dynamic image through the first brightness correction image, the second brightness correction image and the third brightness correction image, and fuse the above three mapping dynamic images to obtain the target dynamic image. Through the complementation of details between images with different brightness, the images with higher brightness use the value of the image with lower brightness more, and the image with lower brightness uses the value of the image with higher brightness more, so that the target dynamic image can be The purpose of preserving more image details and improving the image processing effect.

In one embodiment, as shown in FIG. 4 , performing fusion processing on the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image to obtain the target dynamic image includes:

Step 402: Perform fusion processing on the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image to obtain a fusion processed image.

Specifically, in order to retain more image details, the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image are respectively used for fusion processing to obtain a fusion processed image.

In one embodiment, the first mapping dynamic image, the second mapping dynamic image, and the third mapping dynamic image are respectively low dynamic images with pixel values between 0 and 255, and fusion processing is performed on the above three mapping dynamic images Afterwards, the obtained fusion image is also a low dynamic image with pixel values between 0 and 255.

Step 404, acquiring the image area of the fusion-processed image.

Specifically, although the fusion-processed image retains the highlights and shadow details in the high dynamic range image, in some highlight areas that originally have color information, such as colored signboard light boxes, the corrected images after different brightness corrections will appear due to highlight truncation. different color. For example, a brighter image will be overexposed due to brightness correction, causing the image to turn white. Therefore, the image obtained by the fusion processing method often has a color cast in the highlight color. The image area may be a partial area of the fused image, or may be the entire area of the fused image.

Step 406, obtaining a reference image area.

Specifically, the size of the fused image is the same as that of the second mapped dynamic image. In the second mapped dynamic image, there is an image area corresponding to the fused image, and a reference image area is obtained. The reference image area may be a partial area in the second mapped dynamic image, or may be the entire area in the second mapped dynamic image.

Step 408: Calculate the local mapping gain value of the image region of the fused image relative to the reference image region.

The local mapping gain value means that the mapping value is the mapping gain value corresponding to the image area.

In one embodiment, the local mapping gain value is subjected to inverse gamma transformation between the image region in the fused image and the reference image region in the second mapped dynamic image, and the ratio calculation is performed on the two luminance values after the inverse gamma transformation to obtain The linear gain value of the luminance value of each pixel of the fused image relative to the luminance value of the corresponding pixel of the second mapped dynamic image.

In one embodiment, by calculating the difference between the two luminance values of the to-be-processed image region in the inverse gamma-transformed fused image and the reference image region in the second mapped dynamic image, each of the fused images can be obtained. The linear gain value of the luminance value of the pixel relative to the luminance value of the pixel corresponding to the second mapped dynamic image.

Step 410: Perform tone mapping processing on the first dynamic image according to the local mapping gain value to obtain a target dynamic image.

Specifically, after the local mapping gain value is obtained, tone mapping is performed on the first dynamic image, and after gamma transformation is performed, the first dynamic image is converted into an eight-bit low dynamic range image with a pixel value between 0 and 255.

In one embodiment, the product of the pixel value of the to-be-processed image region of the first dynamic image and the second luminance coefficient correction coefficient corresponding to the corresponding second mapped dynamic image pixel is multiplied by the local mapping gain value of the corresponding pixel position. Operation, and then perform gamma transformation on the pixel value after the gain, and convert it into an eight-bit low-dynamic target dynamic image with a pixel value between 0 and 255. After the above processing, more details of the image can be preserved, the effect of image processing can be improved, and the color of highlights can be more accurate.

In one embodiment, when the pixel value after the gain exceeds the preset pixel value, it is limited to the preset pixel value. For example, when the preset pixel value is limited to 65535, the part of the pixel value after the gain that exceeds 65535 is limited to 65535.

In this embodiment, the fusion processing image is obtained by using the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image, and the to-be-processed image area in the fusion processing image can be processed by using the local mapping gain value. The fused image is then subjected to gamma change to obtain a target dynamic image, which can achieve a target image with more image details preserved after image processing.

In one embodiment, as shown in FIG. 5 , obtaining a statistical value of ambient light intensity includes:

Step 502: Acquire the sensitivity, shutter speed and aperture value corresponding to the first dynamic image.

Among them, the sensitivity refers to the sensitivity of the camera to light when the first dynamic image is acquired. If the sensitivity is too high, the image quality will be affected. Although the brightness of the acquired image will be bright, the sensitivity will be too high if the sensitivity is too high. More noise; shutter speed refers to the opening time of the shutter when using the camera to capture images. The faster the shutter speed, the shorter the opening time, the less light entering the camera, and the darker the image; conversely, the slower the shutter speed, the longer the opening time. The longer, the more light entering the camera, the brighter the image. The aperture value refers to the relative value of the light passing through the camera lens. The smaller the aperture value, the greater the amount of light entering in the same unit time; conversely, the larger the aperture value, the greater the amount of light entering in the same unit time.

Specifically, the statistical value of ambient light intensity has a functional relationship with the sensitivity, shutter speed, and aperture value. To obtain the statistical value of ambient light intensity, it is necessary to first obtain the above-mentioned parameters of sensitivity, shutter speed, and aperture value.

Step 504, obtaining a first parameter value according to the sensitivity, shutter speed and aperture value.

Specifically, after obtaining the sensitivity, shutter speed and aperture value, the first parameter value is obtained through the sensitivity, shutter speed and aperture value. Since the shutter speed is doubled, for example, press 1 second, 1/2 second, 1 /4 second, 1/8 second sequence, the light flux of the lens will be reduced by half; each time the aperture value increases by one stop, for example, 1.4, 2.0, 4.0, 5.6, 8.0, etc., the light flux will also be reduced by half; the shutter speed is based on When the multiple is increased or decreased, the aperture value is multiplied or decreased according to the square root of the fixed value; when the sensitivity is doubled, the amount of light transmitted is reduced by half. Underexposure can be adjusted by setting a larger aperture, slower shutter speed and higher sensitivity value. Avoid overexposure, which can be adjusted by setting a smaller aperture, faster shutter speed and lower ISO value.

In one embodiment, the first parameter value can be represented by a formula, and the formula includes sensitivity, shutter speed and aperture value. The sensitivity is expressed as I, the shutter speed is expressed as s, the aperture value is expressed as a, and the first parameter value is expressed as c, then c can be expressed as: c=I*s/a ²

Step 506: Calculate the parameter ratio between the image brightness statistic and the first parameter.

Specifically, the image brightness statistical value is represented as V0, and the parameter ratio between the image brightness statistical value and the first parameter can be calculated, and the functional relationship between the image brightness statistical value and the acquired image parameter value can be preliminarily determined through the ratio.

In one embodiment, the parameter ratio of the image brightness statistic value to the first parameter can be represented by b:

b=V0/I*s/a ²

Step 508: Perform logarithmic calculation using the parameter ratio as the true number of the logarithmic function to obtain a statistical value of ambient light intensity.

Specifically, the above-mentioned parameter ratio is used as the true number of the logarithmic function to perform logarithmic calculation, and the statistical value of the ambient light intensity can be obtained. The statistical value of ambient light intensity can be expressed as EE, then EE is expressed as: EE=log ₂ b

The ambient light intensity EE is a value greater than 0, so b, which is the base of the logarithmic function, is greater than 1, and the preprocessed image brightness statistic value is greater than the parameter value of the first parameter.

In this embodiment, through the sensitivity, shutter speed, and aperture value corresponding to the first dynamic image, as well as the functional relationship between the three and the statistical value of image brightness, the purpose of obtaining the statistical value of ambient light intensity can be achieved.

In one embodiment, the terminal first obtains the first dynamic image to be processed; obtains the statistical value of the target brightness corresponding to the shooting environment through the statistical value of the image brightness corresponding to the first dynamic image and the statistical value of the ambient light intensity, and obtains the statistical value of the target brightness corresponding to the shooting environment through the statistical value of the target brightness. Determine the target brightness correction coefficient with the image brightness statistic value, and use this target brightness correction coefficient as the first brightness correction parameter; and then form other two brightness correction coefficients by increasing or reducing the brightness on the basis of this first brightness correction coefficient, which are respectively The second brightness correction coefficient and the third brightness correction coefficient are used to process the high dynamic range image through the three brightness correction coefficients to obtain three brightness corrected images, which are respectively the normal images corrected by the first brightness correction coefficient, such as As shown in FIG. 6 ; the darker image corrected by the second brightness correction coefficient is shown in FIG. 7 , and the brighter image corrected by the third brightness correction coefficient is shown in FIG. 8 . After the three images are gamma-transformed, the image pixel values are mapped to red, green, and blue three-channel low-dynamic images with pixel values ranging from 0 to 255. The three low-dynamic images after mapping are then fused to obtain a single image after fusion. Although the fused image retains the highlights and shadow details in the original high dynamic range image, because in some highlight areas that originally have color information, such as colored signboard light boxes, the images corrected by different brightness correction coefficients will appear due to highlight truncation. different color. For example, a brighter image will be overexposed due to brightness correction, causing the image to turn white. The fused image often has a color cast in the highlights. Taking the local brightness information of the fused picture as a reference, and combining the local brightness information corresponding to the darker image, a local tone mapping gain map is obtained. Extract the pixel intensity values of the fused image, and the pixel intensity values of the three darker images in low dynamic range. Perform inverse gamma transformation on the two brightness values, and perform a ratio operation on the two brightness values after inverse gamma transformation, such as division operation, to obtain the brightness value of each pixel of the fused image, which is relative to the brightness value of the corresponding pixel in the darker image. The linear gain value of . The pixel value of the first dynamic image is multiplied by the brightness correction coefficient corresponding to the darker image, and then multiplied by the local tone mapping gain value corresponding to the pixel position to obtain a gain image. When the pixel value in the gain image exceeds the preset pixel value, it is limited to the preset pixel value, and then gamma transform is performed on the pixel value of the gain image, and the pixel value is converted into a pixel value between 0 and 255, with eight red, green and blue channels. Bit low dynamic range images.

It should be understood that although the various steps in the flowcharts of Figures 1-5 are shown in sequence as indicated by the arrows, these steps are not necessarily performed sequentially in the sequence indicated by the arrows. Unless explicitly stated herein, the execution of these steps is not strictly limited to the order, and these steps may be performed in other orders. Moreover, at least a part of the steps in FIGS. 1-5 may include multiple steps or multiple stages. These steps or stages are not necessarily executed and completed at the same time, but may be executed at different times. The execution of these steps or stages The order is also not necessarily sequential, but may be performed alternately or alternately with other steps or at least a portion of the steps or phases within the other steps.

In one embodiment, as shown in FIG. 9, an image processing apparatus 900 is provided, including: a first dynamic image acquisition module 902, an image brightness statistical value acquisition module 904, a target brightness statistical value acquisition module 906, a target brightness correction The coefficient determination module 908, the target brightness correction image determination module 910 and the target dynamic image determination module 912, wherein:

The first dynamic image acquisition module 902 is configured to acquire the first dynamic image to be processed.

The image brightness statistical value acquisition module 904 is configured to acquire the image brightness statistical value corresponding to the first dynamic image.

The target brightness statistical value acquisition module 906 is configured to acquire the ambient light intensity statistical value, and obtain the target brightness statistical value corresponding to the shooting environment according to the ambient light intensity statistical value.

The target brightness correction coefficient determination module 908 is configured to determine the target brightness correction coefficient according to the target brightness statistics value and the image brightness statistics value.

The target brightness correction image determination module 910 is configured to perform brightness correction on the first dynamic image according to the target brightness correction coefficient to obtain a target brightness correction image.

The target dynamic image determination module 912 is configured to perform pixel dynamic range mapping on the target brightness correction image to obtain the target dynamic image.

In one embodiment, the target brightness correction coefficient determination module 910 includes at least one of the following units:

A brightness reduction coefficient acquiring unit, configured to acquire a brightness reduction coefficient as a target brightness correction coefficient when the target brightness statistic value is smaller than the image brightness statistic value.

In one embodiment, the target brightness correction coefficient determination module is further used for:

Calculate the brightness ratio of the target brightness statistic value to the image brightness statistic value;

Taking the luminance ratio as a true number in the logarithmic function, perform logarithmic calculation to obtain a first luminance correction coefficient, wherein the base of the logarithmic function is greater than 1.

In one embodiment, the target brightness correction coefficient determination module 910 is further configured to: perform a reduction process on the first brightness correction coefficient to obtain a second brightness correction coefficient;

The target brightness correction image determination module 910 is further configured to: perform brightness correction on the first dynamic image according to the first brightness correction coefficient, the second brightness correction coefficient, and the third brightness correction coefficient, respectively, to obtain the first brightness correction coefficient corrected by the first brightness correction coefficient. a brightness corrected image, a second brightness corrected image corrected by the second brightness correction coefficient, and a third brightness corrected image corrected by the third brightness correction coefficient;

The target dynamic image determination module 912 is also used to:

Perform pixel dynamic range mapping on the first brightness-corrected image, the second brightness-corrected image, and the third brightness-corrected image, respectively, to obtain a first mapping dynamic image corresponding to the first brightness-corrected image and a second mapping dynamic corresponding to the second brightness-corrected image the image and the third mapping dynamic image corresponding to the third brightness correction image;

The first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image are fused to obtain the target dynamic image.

In one embodiment, the target dynamic image determination module 912 is further configured to:

obtaining the image area of the fusion processing image;

Get the reference image area;

Calculate the local mapping gain value of the image area to be processed relative to the reference image area;

Tone-mapping processing is performed on the first dynamic image according to the local mapping gain value to obtain the target dynamic image.

In one embodiment, an ambient light intensity statistical value acquisition module is further included, configured to acquire the sensitivity, shutter speed, and aperture value corresponding to the first dynamic image;

Calculate the parameter ratio of the image brightness statistical value and the first parameter;

Taking the parameter ratio as the true number of the logarithmic function, the logarithm calculation is performed to obtain the statistical value of the ambient light intensity, where the base of the logarithmic function is greater than 1.

For the specific limitation of the image processing apparatus, reference may be made to the limitation of the image processing method above, which will not be repeated here. Each module in the above-mentioned image processing apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

In one embodiment, a computer device is provided, and the computer device may be a server, and its internal structure diagram may be as shown in FIG. 10 . The computer device includes a processor, memory, and a network interface connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium, an internal memory. The nonvolatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the execution of the operating system and computer programs in the non-volatile storage medium. The database of the computer device is used to store image processing data. The network interface of the computer device is used to communicate with an external terminal through a network connection. The computer program implements an image processing method when executed by a processor.

Those skilled in the art can understand that the structure shown in FIG. 10 is only a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer equipment to which the solution of the present application is applied. Include more or fewer components than shown in the figures, or combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is also provided, including a memory and a processor, where a computer program is stored in the memory, and the processor implements the steps in the foregoing method embodiments when the processor executes the computer program.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, implements the steps in the foregoing method embodiments.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage In the medium, when the computer program is executed, it may include the processes of the above-mentioned method embodiments. Wherein, any reference to memory, storage, database or other media used in the various embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, or optical memory, and the like. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

The technical features of the above embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features It is considered to be the range described in this specification.

The above-mentioned embodiments only represent several embodiments of the present application, and the descriptions thereof are specific and detailed, but should not be construed as a limitation on the scope of the invention patent. It should be pointed out that for those skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which all belong to the protection scope of the present application. Therefore, the scope of protection of the patent of the present application shall be subject to the appended claims.

Claims

An image processing method, characterized in that the method comprises:

obtaining the first dynamic image to be processed;

obtaining the image brightness statistics value corresponding to the first dynamic image;

Obtaining a statistical value of ambient light intensity, and obtaining a statistical value of target brightness corresponding to the shooting environment according to the statistical value of ambient light intensity; the statistical value of ambient light intensity is a statistical value of light intensity of the shooting environment where the first dynamic image is located;

Determine a target brightness correction coefficient according to the target brightness statistic value and the image brightness statistic value;

Perform brightness correction on the first dynamic image according to the target brightness correction coefficient to obtain a target brightness correction image;

Performing pixel dynamic range mapping on the target brightness correction image to obtain a target dynamic image, wherein the pixel dynamic range of the target dynamic image is smaller than the pixel dynamic range of the first dynamic image.
The method according to claim 1, wherein the determining the target brightness correction coefficient according to the target brightness statistic value and the image brightness statistic value comprises at least one of the following steps:

When the target brightness statistic value is greater than the image brightness statistic value, obtain a brightness enhancement coefficient as a target brightness correction coefficient;

When the target brightness statistic value is smaller than the image brightness statistic value, a brightness reduction coefficient is obtained as a target brightness correction coefficient.
The method according to claim 1 or 2, wherein the target brightness correction coefficient comprises a first brightness correction coefficient, and the determining the target brightness correction coefficient according to the target brightness statistical value and the image brightness statistical value comprises: :

Calculate the brightness ratio of the target brightness statistic value and the image brightness statistic value;

Taking the luminance ratio as a true number in a logarithmic function, logarithm calculation is performed to obtain a first luminance correction coefficient, wherein the base of the logarithmic function is greater than 1.
The method according to claim 3, wherein the target brightness correction coefficient further comprises a second brightness correction coefficient and a third brightness correction coefficient; the determining according to the target brightness statistic value and the image brightness statistic value Target brightness correction factors include:

performing a reduction process on the first brightness correction coefficient to obtain a second brightness correction coefficient;

performing increasing processing on the first brightness correction coefficient to obtain a third brightness correction coefficient;

The performing brightness correction on the first dynamic image according to the target brightness correction coefficient to obtain a target brightness correction image includes:

Performing brightness correction on the first dynamic image according to the first brightness correction coefficient, the second brightness correction coefficient, and the third brightness correction coefficient, respectively, to obtain a first brightness corrected by the first brightness correction coefficient a corrected image, a second brightness corrected image corrected by the second brightness correction coefficient, and a third brightness corrected image corrected by the third brightness correction coefficient;

The performing pixel dynamic range mapping on the target brightness correction image to obtain the target dynamic image includes:

Perform pixel dynamic range mapping on the first brightness-corrected image, the second brightness-corrected image, and the third brightness-corrected image, respectively, to obtain a first mapped dynamic image corresponding to the first brightness-corrected image, the The second mapping dynamic image corresponding to the two brightness correction images and the third mapping dynamic image corresponding to the third brightness correction image;

Fusion processing is performed on the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image to obtain a target dynamic image.
The method according to claim 4, wherein the performing fusion processing on the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image to obtain the target dynamic image comprises:

Perform fusion processing on the first mapping dynamic image, the second mapping dynamic image and the third mapping dynamic image to obtain a fusion processed image;

obtaining the image area of the fusion processing image;

Get the reference image area;

Calculate the local mapping gain value of the image area of the fused image relative to the reference image area;

Tone-mapping processing is performed on the first dynamic image according to the local mapping gain value to obtain a target dynamic image.
The method according to claim 5, wherein the obtaining a statistical value of the ambient light intensity comprises:

acquiring the sensitivity, shutter speed and aperture value corresponding to the first dynamic image;

Obtain the first parameter value according to the sensitivity, shutter speed and aperture value;

calculating the parameter ratio of the image brightness statistic to the first parameter;

The parameter ratio is used as the true number of the logarithmic function to perform logarithmic calculation to obtain a statistical value of the ambient light intensity, wherein the base of the logarithmic function is greater than 1.
An image processing device, characterized in that the device comprises:

a first dynamic image acquisition module, configured to acquire the first dynamic image to be processed;

an image brightness statistical value acquisition module, used for acquiring the image brightness statistical value corresponding to the first dynamic image;

a target brightness statistical value acquisition module, configured to acquire a statistical value of ambient light intensity, and obtain a statistical value of target brightness corresponding to the shooting environment according to the statistical value of ambient light intensity;

a target brightness correction coefficient determination module, configured to determine a target brightness correction coefficient according to the target brightness statistic value and the image brightness statistic value;

a target brightness correction image determination module, configured to perform brightness correction on the first dynamic image according to the target brightness correction coefficient to obtain a target brightness correction image;

The target dynamic image determination module is used for performing pixel dynamic range mapping on the target brightness correction image to obtain the target dynamic image.
The device according to claim 7, wherein the target brightness correction coefficient determination module comprises at least one of the following units:

a brightness enhancement coefficient obtaining unit, configured to obtain a brightness enhancement coefficient as a target brightness correction coefficient when the target brightness statistic value is greater than the image brightness statistic value;

A brightness reduction coefficient obtaining unit, configured to obtain a brightness reduction coefficient as a target brightness correction coefficient when the target brightness statistic value is smaller than the image brightness statistic value.
A computer device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, when the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.
A computer-readable storage medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.