Video image conversion method and device based on tone mapping

Abstract

The invention provides a tone mapping-based video image conversion method and apparatus, and a computer storage medium. The method comprises the steps of generating a normalized target histogram of a display image meeting a preset condition according to a preset scene of a video image; calculating target image features according to the normalized target histogram; calculating a brightness evaluation amount according to the video image and the exposure information thereof; confirming an overall brightness control parameter in the tone mapping function according to the brightness evaluation quantity; and performing tone mapping on the video image by using the confirmed tone mapping function. The target image features are obtained by generating the normalized target histogram meeting the preset condition, so that reasonable brightness guidance can be provided for tone mapping; according to the invention, the tone mapping function is confirmed through the brightness evaluation quantity, so that the obtained video image brightness accords with the sense of human eyes, sudden change inconsistent with scene change is not easy to occur, stable control of the video brightness is realized, and the problem that the video brightness obtained by the existing tone mapping method is unstable is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to a video image conversion method and device based on tone mapping, and a computer storage medium. Background Art

[0002] At present, the method of acquiring and displaying high dynamic range video is usually to use a high dynamic range video generation device to capture a series of exposed low dynamic range (LDR) images, and then synthesize the LDR images into HDR high-bitwidth images through high dynamic range synthesis (HDR) technology, and then compress the HDR high-bitwidth images into HDR low-bitwidth images through tone mapping technology, and then use the display device to perform compression mapping to obtain a high dynamic range display image that meets the screen resolution, and finally convert a series of high dynamic range display images into high dynamic range video.

[0003] However, the tone mapping technology currently used usually uses nonlinear mapping, so that the brightness of a series of compressed HDR low-bitwidth images may not be able to continue the brightness continuity of a series of captured low dynamic range images, and thus brightness instability may occur in the final high dynamic range video.

[0004] In addition, in the existing tone mapping technology, the mapping value of the target brightness is relatively subjective and tends to be manually debugged in multiple scenes. It lacks adaptive adjustment and more reasonable target brightness guidance, which can easily lead to unstable brightness of the converted video when applied to video conversion. Summary of the invention

[0005] The object of the present invention is to provide a video image conversion method and device based on tone mapping, and a computer storage medium to solve the problem of unstable video brightness obtained by the existing tone mapping method.

[0006] In order to solve the above technical problems, the present invention provides a video image conversion method based on tone mapping, comprising: According to a preset scene of the video image, a normalized target histogram of the display image that meets preset conditions is generated; Calculate the target image features according to the normalized target histogram; Calculate brightness evaluation quantity based on video image and exposure information thereof; According to the brightness evaluation amount, determine the overall brightness control parameter in the tone mapping function; The confirmed tone mapping function is used to perform tone mapping on the video image to obtain a low-bit-width video image.

[0007] Optionally, in the video image conversion method based on tone mapping, the method of generating a normalized target histogram of a display image that meets preset conditions according to a preset scene of the video image includes: Classify video images into preset scenes; Using a continuous probability density distribution model, the video image in the preset scene is analyzed and processed to obtain a target histogram of the display image that is adapted to the human eye senses; The target histogram is normalized to obtain a normalized target histogram.

[0008] Optionally, in the video image conversion method based on tone mapping, the method for calculating target image features according to the normalized target histogram includes: Using the compression mapping model, the normalized target histogram is subjected to inverse compression mapping to obtain a normalized target histogram after tone mapping; Calculate the target image features based on the normalized target histogram after tone mapping.

[0009] Optionally, in the tone mapping-based video image conversion method, the target image features include one or more of average normalized brightness, spatial brightness distribution, proportion of specific brightness intervals, image edge information, and multi-scale information.

[0010] Optionally, in the video image conversion method based on tone mapping, the method for calculating the brightness evaluation amount according to the video image and its exposure information includes: Acquire exposure information corresponding to the video image, the exposure information including effective average brightness, exposure time and gain; Calculate the brightness evaluation quantity according to the effective average brightness, exposure time and gain; According to the preset scene of the video image, the brightness evaluation amount is matched with the target image features.

[0011] Optionally, in the video image conversion method based on tone mapping, the effective average brightness is the average brightness of the video image within a preset brightness range.

[0012] Optionally, in the video image conversion method based on tone mapping, the method of confirming the overall brightness control parameter in the tone mapping function according to the brightness evaluation amount includes: Establishing a mapping function of the overall brightness control parameter of the tone mapping function with respect to the brightness evaluation amount; Substitute the calculated brightness evaluation value into the mapping function to obtain the corresponding overall brightness control parameter; The obtained overall brightness control parameter is brought into the tone mapping function to obtain a confirmed tone mapping function.

[0013] Optionally, in the video image conversion method based on tone mapping, the method of establishing a mapping function of the overall brightness control parameter of the tone mapping function with respect to the brightness evaluation amount includes: Establishing a relationship function of an overall brightness control parameter of a tone mapping function with respect to a brightness evaluation amount, wherein the relationship function includes a set of unknown parameters; According to the target image features corresponding to the preset scene, the corresponding overall brightness control parameters are calculated; The overall brightness control parameter and the corresponding brightness evaluation quantity are brought into the relationship function to obtain the unknown parameters; The obtained value of the unknown parameter is substituted into the relationship function to obtain a mapping function of the overall brightness control parameter of the tone mapping function with respect to the brightness evaluation amount.

[0014] In order to solve the above technical problems, the present invention further provides a video image conversion device based on tone mapping, which is used to implement the video image conversion method based on tone mapping as described in any one of the above items, and the video image conversion device based on tone mapping includes: A target image feature acquisition module, used to generate a normalized target histogram of a display image that meets preset conditions according to a preset scene of a video image, and calculate target image features according to the normalized target histogram; A tone mapping function generation module is used to calculate a brightness evaluation amount according to the video image and its exposure information, and to confirm an overall brightness control parameter in the tone mapping function according to the brightness evaluation amount, so as to obtain a confirmed tone mapping function; The video image conversion module is used to perform tone mapping on the video image using the confirmed tone mapping function to obtain a low-bit-width video image.

[0015] In order to solve the above technical problems, the present invention also provides a computer storage medium, wherein the computer storage medium stores an executable program; when the executable program is executed, the video image conversion method based on tone mapping as described in any one of the above items is implemented.

[0016] The video image conversion method and device based on tone mapping provided by the present invention, and the computer storage medium include: generating a normalized target histogram of a display image that meets preset conditions according to a preset scene of a video image; calculating target image features according to the normalized target histogram; calculating a brightness evaluation amount according to the video image and its exposure information; confirming the overall brightness control parameter in the tone mapping function according to the brightness evaluation amount; and performing tone mapping on the video image using the confirmed tone mapping function to obtain a low-bitwidth video image. By generating a normalized target histogram that meets preset conditions and then obtaining the target image features, a more reasonable brightness guidance can be provided for tone mapping; the tone mapping function is confirmed by the brightness evaluation amount, so that the brightness of the video image after the final tone mapping not only meets the human eye senses, but also is not prone to sudden changes inconsistent with scene changes, thereby achieving smooth control of video brightness and solving the problem of unstable video brightness obtained by the existing tone mapping method. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flowchart of a video image conversion method based on tone mapping provided in this embodiment; Figure 2 A schematic diagram of the structure of a video image conversion device based on tone mapping provided in this embodiment. DETAILED DESCRIPTION

[0018] The following is a further detailed description of the video image conversion method and device based on tone mapping and the computer storage medium proposed in the present invention in conjunction with the accompanying drawings and specific embodiments. It should be noted that the accompanying drawings are all in a very simplified form and use non-precise proportions, which are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention. In addition, the structure shown in the accompanying drawings is often a part of the actual structure. In particular, the emphasis that each drawing needs to show is different, and sometimes different proportions are used.

[0019] It should be noted that the terms "first", "second", etc. in the specification, claims and drawings of the present invention are used to distinguish similar objects in order to describe the embodiments of the present invention, rather than to describe a specific order or sequence. It should be understood that the structures used in this way can be interchanged under appropriate circumstances. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0020] This embodiment provides a video image conversion method based on tone mapping, such as Figure 1 As shown, including: S1, generating a normalized target histogram of a display image that meets preset conditions according to a preset scene of a video image; S2, calculate the target image features according to the normalized target histogram; S3, calculating a brightness evaluation amount according to the video image and its exposure information; S4, confirming the overall brightness control parameter in the tone mapping function according to the brightness evaluation amount; S5, performing tone mapping on the video image using the confirmed tone mapping function to obtain a low-bit-width video image.

[0021] The video image conversion method based on tone mapping provided in this embodiment can provide more reasonable brightness guidance for tone mapping by generating a normalized target histogram that meets preset conditions and then obtaining target image features. The tone mapping function is confirmed by a brightness evaluation value, so that the brightness of the video image after the final tone mapping not only conforms to the human eye perception, but also is not prone to mutations inconsistent with scene changes, thereby achieving smooth control of video brightness and solving the problem of unstable video brightness obtained by existing tone mapping methods.

[0022] Specifically, in this embodiment, step S1, the method of generating a normalized target histogram of a display image that meets preset conditions according to a preset scene of a video image includes: S11, classifying the video images into preset scenes.

[0023] The preset scenes can be divided into multiple types according to actual needs. For example, in this embodiment, three typical scenes are set as preset scenes, namely: a brighter outdoor scene, a normal brightness scene with a certain amount of light, and an extremely dark scene with no light.

[0024] When classifying video images into preset scenes, the distinction can be made through image information. For example, the larger the histogram integral value, the brighter the scene. Therefore, the histogram integral value range can be divided and the divided range can be matched with the typical scene. The video image can be mapped to different preset scenes by obtaining the histogram integral value of the video image. Of course, in actual applications, the preset scenes can also be divided by the percentage of pixels in each brightness interval of the histogram, the spatial brightness distribution, etc., and this application does not limit this.

[0025] S12, using a continuous probability density distribution model, analyzing and processing the video image in the preset scene to obtain a target histogram of the display image that meets preset conditions.

[0026] In practical applications, the preset conditions can be adapted to the human eye senses to ensure that the video images observed by the human eye have a good display effect, and the measurement criteria for adapting to the human eye senses are well known to those skilled in the art. The continuous probability density distribution model needs to select a continuous probability density distribution model that is adapted to the human eye senses, and the specific needs need to be confirmed based on factors such as application scenarios and image acquisition equipment. The most commonly selected continuous probability density distribution model is the normal distribution model. Of course, those skilled in the art can also choose a more accurate but complex model according to actual needs, and this application does not limit this.

[0027] S13, normalizing the target histogram to obtain a normalized target histogram.

[0028] Specifically, all numbers in the interval range [0, R] of the target histogram are proportionally scaled to the interval range [0, 1], that is, all numbers in the interval range [0, R] are divided by R to obtain a normalized target histogram with an interval range of [0, 1].

[0029] In step S1 of this embodiment, an ideal target histogram is established by using a probability distribution whose brightness distribution conforms to the natural perception of the human eye, so as to provide a more principled and digital brightness guidance for subsequent tone mapping, rather than adjusting parameters by relying on multi-scene experience values, so that the brightness of the final video image is consistent with the brightness change trend of the original video image (LDR image), thereby improving the problem of unstable video brightness.

[0030] Furthermore, in this embodiment, in step S2, the method of calculating the target image features according to the normalized target histogram includes: S21, using the compression mapping model, performing inverse compression mapping on the normalized target histogram to obtain a normalized target histogram after tone mapping.

[0031] Specifically, the compression mapping model is a compression mapping model used by the video display device. For example, where β is a positive number greater than 1.

[0032] Let the normalized target histogram be hF. If the interval number M1 of the normalized target histogram corresponding to hF is 4095, that is, M1=[0,1 / 4095,2 / 4095,……,4094 / 4095,1], then bring each number of M1 into the y of the compression mapping function, that is:

[0033] at this time, .

[0034] After the inverse compression mapping, the normalized target histogram after tone mapping is determined according to the number of intervals M2 of the normalized target histogram after tone mapping. Assuming M2 is 255, the normalized target histogram after tone mapping is denoted as hTM. Then, the 4095 intervals of hF need to be re-divided into 255 intervals of hTM, that is, M2=[0,1 / 255,2 / 255,……,254 / 255,1]. If the interval of hF is If it falls within the hTM interval [0,1 / 255], the first number in the normalized target histogram after tone mapping is hTM[0] = hF[0] + hF[1] + … + hF[k], where k is a value between [0,4095]. Subsequent values ​​are calculated similarly to obtain the normalized target histogram after tone mapping.

[0035] S22, calculating target image features according to the normalized target histogram after tone mapping.

[0036] In practical applications, target image features include one or more of average normalized brightness, spatial brightness distribution, proportion of specific brightness intervals, image edge information, and multi-scale information.

[0037] In this embodiment, the target image feature only includes the average normalized brightness as an example. According to the normalized target histogram after tone mapping, the formula for calculating the target image feature is:

[0038] Where N represents the sequence number of the typical scene (preset scene), represents the average normalized brightness corresponding to the typical scene (preset scene), and hTM[k] represents the kth value in the normalized target histogram after tone mapping corresponding to the typical scene (preset scene).

[0039] Of course, when the target image features also include other features, those skilled in the art can obtain the calculation method of other target image features according to the above examples, and this application will not go into details.

[0040] In step S2 of this embodiment, the target image features of the tone mapping are calculated by inverse mapping of the display device, which can provide a more principled and digital brightness guidance for the tone mapping instead of adjusting the parameters entirely by relying on multi-scene experience values, so that the brightness of the final video image is consistent with the brightness change trend of the original video image (LDR image), thereby improving the problem of unstable video brightness.

[0041] Furthermore, in this embodiment, in step S3, the method for calculating the brightness evaluation value according to the video image and its exposure information includes: S31, obtaining exposure information corresponding to the video image, where the exposure information includes effective average brightness, exposure time and gain.

[0042] Preferably, in order to eliminate the influence of dark noise and highlight overexposure information, in this embodiment, the effective average brightness is the average brightness of the video image within the preset brightness range [V1, V2]. In practical applications, the preset brightness range can be manually set according to the sensor characteristics of the video shooting device (high dynamic range video generation device) (such as sensitivity, noise, etc.). Usually, the value of V1 is small, and the value of V2 is close to the maximum value of the brightness of a single frame of the video image. For example, if the data range collected by the sensor is 0~4095, V1 can be set to 30 and V2 can be set to 3900.

[0043] In this embodiment, the calculation formula of the effective average brightness can be expressed as:

[0044] Where NUM represents the total number of pixels in the video image, and V(i) represents the brightness of the current pixel; Indicates that when the brightness of the current pixel is within the preset brightness range, the value is 1, otherwise it is 0.

[0045] S32, calculating a brightness evaluation value according to the effective average brightness, exposure time and gain.

[0046] Specifically, in this embodiment, the calculation formula of the brightness evaluation value is:

[0047] Wherein, Vm represents the effective average brightness, te represents the exposure time, and g represents the gain.

[0048] It can be seen from the calculation formula of the brightness evaluation value that when the sensor is fixed, the value of this value is mainly determined by the scene of the video image itself, thereby ensuring smooth control of the image brightness.

[0049] S33, according to the preset scene of the video image, the brightness evaluation amount is matched with the target image feature.

[0050] In step S3 of this embodiment, a model of the brightness evaluation value Lv related to the scene parameters is constructed so that the final mapped target brightness not only conforms to the natural perception of the human eye, but also is stable and not prone to mutations inconsistent with scene changes.

[0051] Furthermore, in this embodiment, in step S4, the method of confirming the overall brightness control parameter in the tone mapping function according to the brightness evaluation amount includes: S41, establishing a mapping function of the overall brightness control parameter of the tone mapping function with respect to the brightness evaluation amount.

[0052] Specifically, in this embodiment, firstly, a relationship function of the overall brightness control parameter of the tone mapping function with respect to the brightness evaluation amount is established, wherein the relationship function includes a group of unknown parameters.

[0053] Assume the tone mapping function is , and its overall brightness control parameter is , taking a simple tone mapping function as an example, the tone mapping function is expressed as:

[0054] in, Represents the normalized brightness of the video image; Represents the normalized brightness of the tone-mapped video image (low-bitwidth video image); Represents the overall brightness control parameter, which is used to control the brightness of image conversion.

[0055] Then the relationship function can be expressed as , where a set of unknown parameters is expressed as , the number of unknown parameters should be consistent with the number of preset scenarios to facilitate the subsequent calculation of unknown parameters.

[0056] Then, according to the target image features corresponding to the preset scene, the corresponding overall brightness control parameters are calculated.

[0057] Still taking the above example, the number of preset scenes is 3, and the target image feature is the average normalized brightness. Through the above steps S1 to S3, the normalized brightness of the input video image has been known. and target image features , so the tone mapping function can be used to obtain the overall brightness control parameters corresponding to the three typical scenes , which can be expressed as:

[0058] Wherein, j represents the sequence number of the current preset scene.

[0059] Of course, if the number of preset scenes is N, then N overall brightness control parameters are obtained accordingly. , denoted as .

[0060] Next, the overall brightness control parameter and the corresponding brightness evaluation amount are brought into the relationship function to obtain the unknown parameters.

[0061] Specifically, according to the overall brightness control parameters and the corresponding brightness evaluation Do curve fitting and build a model with N unknown variables In this embodiment, still taking N as 3 as an example, based on the log-type processing method of brightness by the human eye, a relatively simple continuous curve model is adopted:

[0062] In this example, the resulting relationship function The corresponding A[1]=0.8, A[2]=2, A[3]=-3.

[0063] Finally, the value of the unknown parameter obtained is brought into the relationship function to obtain a mapping function of the overall brightness control parameter of the tone mapping function with respect to the brightness evaluation amount.

[0064] Because the mapping function is inferred from the target brightness on the display device that meets the needs of the human eye, and when the sensor is fixed, it is mainly determined by the brightness of the scene itself. Therefore, the brightness after tone mapping compression not only meets the needs of the human eye, but is also stable and does not change suddenly, which can improve the brightness instability of high dynamic range video imaging.

[0065] S42, bringing the calculated brightness evaluation amount into the mapping function to obtain the corresponding overall brightness control parameter.

[0066] Specifically, when the overall brightness control parameter is obtained About the brightness evaluation The mapping function Then, in practical applications, the brightness evaluation value calculated in step S3 can be Bring in the mapping function In order to obtain the brightness evaluation value The corresponding overall brightness control parameters .

[0067] S43, bringing the obtained overall brightness control parameter into the tone mapping function to obtain a confirmed tone mapping function.

[0068] The overall brightness control parameters calculated in the previous step are Bring in the tone mapping function ), we can get the tone mapping function with adaptive overall brightness control parameters. ).

[0069] In step S4 of this embodiment, unknown parameters are solved by substituting the target image features of the preset scene into the tone mapping function and the relationship function to obtain a new mapping function. The function introduces a scene brightness evaluation value Lv, so that the overall brightness of the tone mapping can be adaptively controlled according to the target brightness requirement, so that the final mapped target brightness not only conforms to the natural perception of the human eye, but also is stable and not prone to mutations inconsistent with scene changes.

[0070] Of course, although this embodiment only illustrates the implementation process of the proposed video image conversion method based on tone mapping with three typical scenes and one target image feature, those skilled in the art can, inspired by the above content, understand the video image conversion method when there are other numbers of typical scenes and multiple target image features, and this application will not go into details.

[0071] Furthermore, in this embodiment, in step S5, tone mapping is performed on the video image using the confirmed tone mapping function to obtain a video image with a low bit width.

[0072] Specifically, in this embodiment, for each pixel of the video image, its input brightness It is known that the overall brightness control parameter It can be obtained through the above steps, then through the tone mapping function ) can obtain the brightness of the pixel after tone mapping . Acts on the input image (video image) , you can get the output image (tone-mapped image, low-bitwidth video image) , taking the classic mapping relationship as an example, the mapping relationship between the input image and the output image can be expressed as:

[0073] The video image conversion method based on tone mapping provided in this embodiment provides a more objective target brightness evaluation method, and guides the adaptive brightness adjustment of the tone mapping of the high dynamic range video to be stable, which is consistent with the brightness change trend of the LDR image, and improves the problem of unstable video brightness. Among them: a histogram is generated through a continuous probability density distribution model to obtain a better brightness distribution of the target image; the ideal image brightness distribution after tone mapping is accurately obtained through inverse compression mapping and the ideal image distribution on the display device side; a corresponding function model is established for the overall brightness control parameter, and the brightness performance of the tone mapping output image is linked with the collected input data and device-related information. The mapping function is substituted and solved by the calibration values ​​of the target image features, overall brightness control parameters and other parameters of the typical scene, and a tone mapping function with more parameter adaptive control and a composite multi-function model is obtained, thereby ensuring that the target brightness of the output image has objective model guidance and changes continuously and smoothly.

[0074] This embodiment also provides a video image conversion device based on tone mapping, which is used to implement the video image conversion method based on tone mapping as described above. Figure 2 As shown, the video image conversion device based on tone mapping includes: A target image feature acquisition module, used to generate a normalized target histogram of a display image that meets preset conditions according to a preset scene of a video image, and calculate target image features according to the normalized target histogram; A tone mapping function generation module is used to calculate a brightness evaluation amount according to the video image and its exposure information, and to confirm an overall brightness control parameter in the tone mapping function according to the brightness evaluation amount, so as to obtain a confirmed tone mapping function; The video image conversion module is used to perform tone mapping on the video image using the confirmed tone mapping function to obtain a low-bit-width video image.

[0075] The video image conversion device based on tone mapping provided in this embodiment generates a normalized target histogram that meets preset conditions through a target image feature acquisition module, and then obtains the target image features, which can provide more reasonable brightness guidance for tone mapping; the brightness evaluation amount is calculated through a tone mapping function generation module to confirm the tone mapping function, so that the brightness of the video image after the final tone mapping not only meets the human eye perception, but also is not prone to sudden changes inconsistent with scene changes, thereby achieving smooth control of the video brightness and solving the problem of unstable video brightness obtained by the existing tone mapping method.

[0076] Furthermore, this embodiment further provides a computer storage medium, wherein the computer storage medium stores an executable program; when the executable program is executed, the above-mentioned video image conversion method based on tone mapping is implemented.

[0077] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other. In addition, the different parts between the various embodiments can also be used in combination with each other, and the present invention is not limited to this.

[0078] The video image conversion method and device based on tone mapping provided in this embodiment, and the computer storage medium include: generating a normalized target histogram of the display image that meets preset conditions according to the preset scene of the video image; calculating the target image features according to the normalized target histogram; calculating the brightness evaluation amount according to the video image and its exposure information; confirming the overall brightness control parameters in the tone mapping function according to the brightness evaluation amount; and performing tone mapping on the video image using the confirmed tone mapping function to obtain a low-bitwidth video image. By generating a normalized target histogram that meets the preset conditions and then obtaining the target image features, a more reasonable brightness guidance can be provided for the tone mapping; the tone mapping function is confirmed by the brightness evaluation amount, so that the brightness of the video image after the final tone mapping not only meets the human eye perception, but also is not prone to sudden changes inconsistent with the scene changes, thereby achieving smooth control of the video brightness and solving the problem of unstable video brightness obtained by the existing tone mapping method.

[0079] The above description is only a description of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention. Any changes or modifications made by a person skilled in the art in the field of the present invention based on the above disclosure shall fall within the scope of protection of the claims.

Claims

1. A video image conversion method based on tone mapping, characterized in that: include: According to a preset scene of the video image, a normalized target histogram of the display image that meets preset conditions is generated; Calculate the target image features according to the normalized target histogram; Calculate brightness evaluation quantity based on video image and exposure information thereof; According to the brightness evaluation amount, determine the overall brightness control parameter in the tone mapping function; The confirmed tone mapping function is used to perform tone mapping on the video image to obtain a low-bit-width video image.

2. The video image conversion method based on tone mapping according to claim 1, characterized in that: The method for generating a normalized target histogram of a display image that meets preset conditions according to a preset scene of a video image includes: Classify video images into preset scenes; Analyze and process the video image in the preset scene using the continuous probability density distribution model to obtain a target histogram of the display image that meets the preset conditions; The target histogram is normalized to obtain a normalized target histogram.

3. The video image conversion method based on tone mapping according to claim 1, characterized in that: The method for calculating target image features according to the normalized target histogram includes: Using the compression mapping model, the normalized target histogram is subjected to inverse compression mapping to obtain a normalized target histogram after tone mapping; Calculate the target image features based on the normalized target histogram after tone mapping.

4. The video image conversion method based on tone mapping according to claim 3 is characterized in that: The target image features include one or more of average normalized brightness, spatial brightness distribution, specific brightness interval proportion, image edge information, and multi-scale information.

5. The video image conversion method based on tone mapping according to claim 1, characterized in that: The method for calculating the brightness evaluation amount according to the video image and its exposure information includes: Acquire exposure information corresponding to the video image, the exposure information including effective average brightness, exposure time and gain; Calculate the brightness evaluation quantity according to the effective average brightness, exposure time and gain; According to the preset scene of the video image, the brightness evaluation amount is matched with the target image features.

6. The video image conversion method based on tone mapping according to claim 5, characterized in that: The effective average brightness is the average brightness of the video image within a preset brightness range.

7. The video image conversion method based on tone mapping according to claim 5, characterized in that: The method for determining the overall brightness control parameter in the tone mapping function according to the brightness evaluation amount includes: Establishing a mapping function of the overall brightness control parameter of the tone mapping function with respect to the brightness evaluation amount; Substitute the calculated brightness evaluation value into the mapping function to obtain the corresponding overall brightness control parameter; The obtained overall brightness control parameter is brought into the tone mapping function to obtain a confirmed tone mapping function.

8. The video image conversion method based on tone mapping according to claim 7, characterized in that: The method for establishing a mapping function of the overall brightness control parameter of the tone mapping function with respect to the brightness evaluation amount comprises: Establishing a relationship function of an overall brightness control parameter of a tone mapping function with respect to a brightness evaluation amount, wherein the relationship function includes a set of unknown parameters; According to the target image features corresponding to the preset scene, the corresponding overall brightness control parameters are calculated; The overall brightness control parameter and the corresponding brightness evaluation quantity are brought into the relationship function to obtain the unknown parameters; The obtained value of the unknown parameter is substituted into the relationship function to obtain a mapping function of the overall brightness control parameter of the tone mapping function with respect to the brightness evaluation amount.

9. A video image conversion device based on tone mapping, used to implement the video image conversion method based on tone mapping as claimed in any one of claims 1 to 8, characterized in that: The video image conversion device based on tone mapping comprises: A target image feature acquisition module, used to generate a normalized target histogram of a display image that meets preset conditions according to a preset scene of a video image, and calculate target image features according to the normalized target histogram; A tone mapping function generation module is used to calculate a brightness evaluation amount according to the video image and its exposure information, and to confirm an overall brightness control parameter in the tone mapping function according to the brightness evaluation amount, so as to obtain a confirmed tone mapping function; The video image conversion module is used to perform tone mapping on the video image using the confirmed tone mapping function to obtain a low-bit-width video image.

10. A computer storage medium, characterized in that: The computer storage medium stores an executable program; when the executable program is executed, the video image conversion method based on tone mapping as described in any one of claims 1 to 8 is implemented.

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