CN116801108A

CN116801108A - Method and device for determining exposure parameters

Info

Publication number: CN116801108A
Application number: CN202310881706.2A
Authority: CN
Inventors: 张立嵩; 董洪涛; 华剑雄; 王志礼
Original assignee: Beijing Jingwei Hirain Tech Co Ltd
Current assignee: Beijing Jingwei Hirain Tech Co Ltd
Priority date: 2023-07-18
Filing date: 2023-07-18
Publication date: 2023-09-22

Abstract

The embodiment of the application provides a method and a device for determining exposure parameters, which are used for correcting an original image obtained by acquisition equipment to obtain gray values of all pixel points in the original image, correcting the gray values of all pixel points in the original image by using a preset number of correction values to obtain exposure evaluation values respectively corresponding to a preset number of Zhang Jiaozheng images, determining a target correction value based on the exposure evaluation values respectively corresponding to a preset number Zhang Jiaozheng of images, wherein the target correction value is a correction value corresponding to a correction image with the largest exposure evaluation value, and determining a target exposure parameter value based on a current exposure parameter value and the target correction value. The embodiment of the application improves the determination efficiency of the exposure parameter value.

Description

Method and device for determining exposure parameters

Technical Field

The embodiment of the application relates to the technical field of photoelectricity, in particular to a method and a device for determining exposure parameters.

Background

Vehicle auxiliary driving systems are widely used in the field of automobile driving, and in the automatic driving process of an automobile, information in an acquired image is often required to be identified through the auxiliary driving system so as to provide auxiliary information for automatic driving of the automobile. The imaging quality of the image affects the recognition result of the vehicle auxiliary driving system to a certain extent, and the imaging quality of the image has a certain relation with the exposure parameter value of the acquisition device, so that the determination of the proper exposure parameter is important for the auxiliary function of the vehicle auxiliary system.

Currently, the determining process of the exposure parameter value is that an initial exposure parameter value is set for the acquisition device, image acquisition is performed based on the initial exposure parameter value to obtain brightness information of an acquired image, the brightness information is compared with preset target brightness information, and a brightness information difference value is determined, so that the exposure parameter value of the acquisition device is gradually adjusted based on the brightness information difference value until the brightness information of the image acquired by the acquisition device based on the adjusted exposure parameter value meets the requirement of the target brightness information.

In the implementation process, the exposure parameter value of the acquisition equipment needs to be adjusted for multiple times, and the adjustment process is complicated, so that the adjustment efficiency of the exposure parameter value is low.

Disclosure of Invention

The embodiment of the application provides a method and a device for determining exposure parameters, which can increase the adjustment efficiency of exposure parameter values.

In one aspect, an embodiment of the present application provides a method for determining an exposure parameter, where the method includes:

preprocessing the obtained original image to obtain gray values of all pixel points in the original image,

respectively correcting gray values of all pixel points in the original image by using a preset number of correction values to obtain exposure evaluation values respectively corresponding to the preset number of Zhang Jiaozheng images,

determining a target correction value based on the exposure evaluation values respectively corresponding to the preset number Zhang Jiaozheng of images, wherein the target correction value is the correction value corresponding to the correction image with the largest exposure evaluation value,

a target exposure parameter value is determined based on the current exposure parameter value and the target correction value.

In another aspect, an embodiment of the present application provides an apparatus for determining an exposure parameter, where the apparatus includes:

a processing module for preprocessing the obtained original image to obtain the gray value of each pixel point in the original image,

a correction module for correcting the gray value of each pixel point in the original image by using the correction value of the preset number to obtain the exposure evaluation value corresponding to the image of the preset number Zhang Jiaozheng,

and the determining module is used for determining a target correction value based on the exposure evaluation values respectively corresponding to the preset number Zhang Jiaozheng of images, wherein the target correction value is the correction value corresponding to the correction image with the largest exposure evaluation value, and determining a target exposure parameter value based on the current exposure parameter value and the target correction value.

In yet another aspect, an embodiment of the present application provides a computing device, the computing device comprising: comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are operable to be invoked by the processing component to perform a method of determining exposure parameters as described in the first aspect.

In still another aspect, an embodiment of the present application provides a computer storage medium storing a program, where the program is executed to implement the method for determining an exposure parameter according to the first aspect.

The embodiment of the application provides a method and a device for determining exposure parameters, which are used for correcting an original image obtained by acquisition equipment to obtain gray values of all pixel points in the original image, correcting the gray values of all pixel points in the original image by using a preset number of correction values to obtain exposure evaluation values respectively corresponding to a preset number of Zhang Jiaozheng images, determining a target correction value based on the exposure evaluation values respectively corresponding to a preset number of Zhang Jiaozheng images, wherein the target correction value is a correction value corresponding to a correction image with the largest exposure evaluation value, and determining the target correction value based on the current exposure parameter value and the target correction value in a mode of adjusting the exposure parameter value based on image brightness compared with the prior art because the target correction value is a correction value corresponding to the correction image with the largest exposure evaluation value.

Drawings

In order to more clearly illustrate the technical solution of the embodiments of the present application, the drawings that are needed to be used in the embodiments of the present application will be briefly described, and it is possible for a person skilled in the art to obtain other drawings according to these drawings without inventive effort.

FIG. 1 is a flowchart of a method for determining exposure parameters according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a computing device provided by an embodiment of the present application;

FIG. 3 is a flowchart of a method for determining exposure parameters according to an embodiment of the present application;

FIG. 4 is a block diagram of an exposure parameter determining apparatus according to an embodiment of the present application;

FIG. 5 is a schematic diagram of a computing device according to an embodiment of the present application.

Detailed Description

Features and exemplary embodiments of various aspects of embodiments of the present application will be described in detail below, and in order to make the objects, technical solutions and advantages of the embodiments of the present application more apparent, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings and the detailed embodiments. It should be understood that the particular embodiments described herein are intended to be illustrative of the embodiments of the application and are not intended to be limiting of the embodiments of the application. It will be apparent to one skilled in the art that embodiments of the application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the embodiments by showing examples of the embodiments of the application.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

In order to solve the problems in the prior art, the embodiment of the application provides a method and a device for determining exposure parameters. The method for determining exposure parameters provided by the embodiment of the application is first described below.

Fig. 1 is a flow chart illustrating a method for determining exposure parameters according to an embodiment of the present application. As shown in fig. 1, the performing device of the method may be a controller, and the method may include:

101. preprocessing the obtained original image to obtain the gray value of each pixel point in the original image.

Wherein the original image may be acquired by an acquisition device in the vehicle based on the initial exposure parameter values.

In some embodiments, the process of preprocessing the original image may be implemented as: preprocessing an original image to obtain an RGB image of the original image, and determining gray values of color channels of pixels in the acquired image based on the RGB image.

The preprocessing may be any one of black level correction, dead pixel correction, and color interpolation. In some embodiments, RGB represents three color channels of red, green and blue respectively, the value range of the pixel in each channel is 0-255, and the gray value of each color channel of each pixel in the acquired image is obtained by normalizing to 0-1.

102. And respectively correcting the gray values of all pixel points in the original image by using a preset number of correction values to obtain exposure evaluation values respectively corresponding to the preset number of Zhang Jiaozheng images.

The exposure evaluation value may be a sum of gradient values of pixels in the corrected image.

In order to obtain images with different brightness, the gray value of each pixel point in the original image can be corrected, the corrected images with different brightness can be obtained by setting different correction values, the gray value of each pixel in the corrected images can be obtained, and the value range of the correction values can be [1/1.7,1.7].

Further, the gray value of each pixel in the corrected image may be converted to obtain a gradient value of each pixel in the corrected image, and the gradient values of each pixel in the corrected image may be summed to obtain an exposure evaluation value of the corrected image.

It is understood that each correction value can be flexibly selected according to actual conditions.

103. And determining a target correction value based on the exposure evaluation values respectively corresponding to the preset number Zhang Jiaozheng of images.

The target correction value is a correction value corresponding to the correction image having the largest exposure evaluation value.

In some embodiments, after determining the exposure evaluation values corresponding to the preset number Zhang Jiaozheng of images respectively, determining a maximum exposure evaluation value from the preset number of exposure evaluation values, determining a correction image corresponding to the maximum exposure evaluation value, acquiring a correction value of the correction image, and determining the correction value as a target correction value.

It is understood that the larger the exposure evaluation value is, the better the exposure effect of the image is, so that the target correction value is determined by the maximum exposure evaluation value, and further, the target exposure parameter value obtained based on the target correction value is used as the exposure of the acquisition apparatus, and the image with the better exposure effect can be acquired.

104. A target exposure parameter value is determined based on the current exposure parameter value and the target correction value.

In some embodiments, the controller outputs an initial exposure parameter value to the acquisition device, and the acquisition device may acquire the corresponding original image based on the initial exposure parameter value, so that the initial exposure parameter value is a current exposure parameter value, and further, may determine a target exposure parameter value based on the current exposure parameter value and the target correction value.

In some embodiments, the controller determines that the register parameter used by the target exposure parameter value is inconsistent with a register parameter that can be identified by the acquisition device, and therefore, the register parameter may also be normalized, so that the normalized target exposure parameter value is sent to the acquisition device.

For example, if the controller determines that the register parameter used for the target exposure parameter value is binary and the register parameter that the acquisition device can recognize is hexadecimal, then the target exposure parameter value needs to be converted into the hexadecimal register parameter.

The embodiment of the application provides a method for determining exposure parameters, which is characterized in that an original image obtained by acquisition equipment is subjected to correction processing to obtain gray values of all pixel points in the original image, the gray values of all pixel points in the original image are respectively corrected by using correction values of preset quantity to obtain exposure evaluation values respectively corresponding to images of the preset quantity Zhang Jiaozheng, a target correction value is determined based on the exposure evaluation values respectively corresponding to images of the preset quantity Zhang Jiaozheng, the target correction value is a correction value corresponding to a correction image with the largest exposure evaluation value, and a target exposure parameter value is determined based on a current exposure parameter value and the target correction value. The embodiment of the application increases the determination efficiency of the exposure parameter value.

In some embodiments, the correcting the gray values of the pixels in the original image by using the preset number of correction values to obtain the exposure evaluation values corresponding to the preset number of Zhang Jiaozheng images respectively may be implemented as: the gray values of all pixels in the original image are respectively corrected based on a preset number of correction values to obtain gray values of all pixels of a preset number of corrected images, the gradient values of all pixels in the corrected image are determined based on the gray values of all pixels of any corrected image for any corrected image, and the exposure evaluation values of the corrected image are determined based on the gradient values of all pixels in the corrected image to obtain exposure evaluation values corresponding to a preset number of Zhang Jiaozheng images respectively.

In some embodiments, the gray values of the pixels in the original image are corrected based on a preset number of correction values, so that the gray values of the pixels in the preset number of corrected images satisfy the following relationship:

wherein ,I_out Is to correct the gray value of each pixel point in the image, I _in Is the gray value of each pixel in the original image, and gamma is the correction value.

The gray values of all pixel points in the original image can be converted through the relation, so that the corrected images with different gray values are converted, wherein the gray values are related to the brightness of the image, and a plurality of corrected images with different brightness of the image can be obtained.

In some embodiments, the determining, based on the gray values of the pixels of the any one of the corrected images, that the gradient values of the pixels in the corrected image satisfy the following relationship:

N＝log(λ(1-δ))

wherein ,for the gradient value of the ith pixel point in the corrected image, the value range [0, 1] is taken]，m _i For the gray value of the ith pixel point in the corrected image, lambda is a first adjustment coefficient for adjusting the gradient value +.>Delta is the gray value threshold value, and the value range is 0.2-0.4]。

It will be appreciated that it is only meaningful to calculate the gradient value for the pixel if the gray value is greater than the gray value threshold, and therefore the gradient value for the pixel can be calculated if the gray value is greater than the gray value threshold and the gradient value for the pixel can be zero if the gray value is less than the gray value threshold.

Based on the gradient value of each pixel point in the corrected image, determining that the exposure evaluation value of the corrected image meets the following relation:

wherein M is an exposure evaluation value of the corrected image,and the gradient value of the ith pixel point in the corrected image.

In some embodiments, due to the acquisition environment, the exposure evaluation value of a certain corrected image obtained by using the relationship is inconsistent with the actual exposure evaluation measurement value of the image, and in this case, the first adjustment coefficient may be adjusted so that the exposure evaluation value of the certain corrected image is consistent with the actual exposure evaluation measurement value of the image.

In some embodiments, the first adjustment factor is adjusted as follows: and acquiring an exposure evaluation measurement value and the exposure evaluation value of any correction image, if the exposure evaluation measurement value is consistent with the exposure evaluation value, not adjusting a first adjustment coefficient, if the exposure evaluation measurement value is larger than the exposure evaluation value, increasing the first adjustment coefficient based on the difference value between the exposure evaluation measurement value and the exposure evaluation value, and if the exposure evaluation measurement value is smaller than the exposure evaluation value, decreasing the first adjustment coefficient based on the difference value between the exposure evaluation measurement value and the exposure evaluation value.

Wherein the exposure evaluation measurement value can be acquired by a measuring device, the gradient values of the pixels in the correction image are summed to obtain the exposure evaluation value of the correction image, the exposure evaluation measurement value is compared with the exposure evaluation value, if the exposure evaluation measurement value is consistent with the exposure evaluation value, the first adjustment coefficient is free of problems, the exposure evaluation measurement value is larger than the exposure evaluation value, the calculated exposure parameter value is problematic, and the relationship is known,the larger M is, the larger λ is, +.>The larger the exposure evaluation measurement value is, therefore, larger than the exposure evaluation value, which means that the exposure evaluation value needs to be increased, λ is increased, thereby ensuring that the exposure evaluation measurement value coincides with the exposure evaluation value.

Based on the same reason, the exposure evaluation measurement value is smaller than the exposure evaluation value, which means that the exposure evaluation value needs to be reduced, and λ is reduced, so that the exposure evaluation measurement value is consistent with the exposure evaluation value.

In some embodiments, the determining a target exposure parameter value based on the current exposure parameter value and the target correction value satisfies the following relationship:

wherein ,E_t+1 For the target exposure parameter value, alpha is a preset constant, K _p For the second adjustment coefficientFor the target exposure parameter value, E _t Is the current exposure parameter value.

wherein ,indicating that the current correction value is larger, the obtained target exposure parameter value may be larger, and correspondingly, the obtained target exposure parameter value needs to be reduced correspondingly>Indicating that the current correction value is smaller, the obtained target exposure parameter value may be smaller, and then the obtained target exposure parameter value needs to be correspondingly increased.

The second adjustment coefficient is adjusted as follows: and determining an exposure parameter adjustment value based on the target exposure parameter value and the current exposure parameter value, acquiring a preset exposure parameter difference threshold range, and adjusting the second adjustment coefficient based on the exposure parameter adjustment value and the exposure parameter difference threshold range.

It should be noted that if the difference between the target exposure parameter value and the current exposure parameter value determined based on the above relationship is too large, an overshoot phenomenon may occur, and if the difference is too small, an out-of-place adjustment may occur, and multiple adjustments are required. Therefore, after determining the target exposure parameter value, it is further necessary to determine an exposure parameter adjustment value based on the target exposure parameter value and the current exposure parameter value, and compare a preset exposure parameter difference threshold range with the exposure parameter adjustment value, if the exposure parameter adjustment value is greater than a maximum threshold value of the exposure parameter difference threshold range, it is indicated that the exposure parameter adjustment value is too large, then the exposure parameter adjustment value needs to be reduced, and correspondingly, if the exposure parameter adjustment value is less than a minimum threshold value of the exposure parameter difference threshold range, then the exposure parameter adjustment value needs to be increased.

It is understood that the exposure parameter adjustment value is a positive value.

Assuming that the target exposure parameter value is less than the current exposure parameter value, the exposure parameter adjustment value may be the current exposure parameter value minus the target exposure parameter value. If the exposure parameter adjustment value needs to be reduced, the target exposure parameter value needs to be reduced, and as the second adjustment coefficient is larger, the target exposure parameter value can be reduced by reducing the value of the second adjustment coefficient as the second adjustment coefficient is larger. Correspondingly, if the exposure parameter adjustment value needs to be increased, the target exposure parameter value can be increased by increasing the value of the second adjustment coefficient.

The exposure parameter adjustment value may be the target exposure parameter value minus the current exposure parameter value, assuming that the target exposure parameter value is greater than the current exposure parameter value. If the exposure parameter adjustment value needs to be decreased, the target exposure parameter value needs to be increased, which may be increased by increasing the value of the second adjustment coefficient. Correspondingly, if the exposure parameter adjustment value needs to be reduced, the target exposure parameter value can be reduced by reducing the value of the second adjustment coefficient.

Wherein, the adjusting range of the second adjusting coefficient can be [ 0.9-1.1 ].

In order to further explain the above method for determining the exposure parameters, fig. 2 shows a schematic structural diagram of an electronic device according to an embodiment of the present application, where the electronic device may be a mobile phone, a vehicle, a PC terminal, or the like. As shown in fig. 2, the electronic device may include a controller 1 and a camera 6. Further, the controller 1 may include: an exposure control module 2, a gamma fitting module 3, a gradient calculation module 4 and an image information statistics module 5.

The communication modes between the camera 6 and the controller 1 can include an MIPI/LVDS/GMSL communication mode and an I2C communication mode, and the MIPI/LVDS/GMSL communication mode can be used for the camera 6 to communicate with the image information statistics module 5 in the controller 1, and can be used for transmitting original image information at high speed. The I2C communication may be used for bi-directional communication between the camera 6 and the exposure control module 2 in the controller 1, and may be used for transmitting control signals at low speed.

The image information statistics module 5 may be configured to process raw image data of the camera, and perform processing operations such as black level correction, dead pixel correction, and image interpolation on the raw image of the camera, so as to convert the raw image data into RGB data.

The gradient calculating module 4 may be configured to correct the acquired original image to obtain a preset number of corrected images, and acquire gray values of pixels in the preset number of corrected images.

The gamma fitting module 3 may be configured to calculate a gradient value of each pixel in the preset number of correction images based on a gray value of each pixel in the preset number of correction images, calculate an exposure evaluation value of each correction image based on a gradient value of each pixel in the preset number of correction images, determine a maximum exposure evaluation value, and determine a correction value of the correction image corresponding to the maximum exposure evaluation value as the target correction value.

The exposure control module 2 may be configured to write an initial exposure parameter value into the camera 6 through the I2C bus under the condition that the camera 6 is started, determine a target exposure parameter value based on the initial exposure parameter value and the target correction value, convert the target exposure parameter value into a register parameter value that can be identified by the camera, and send the target exposure parameter value converted through the I2C bus to the camera.

Referring to fig. 2, fig. 3 shows a flowchart of a method for determining exposure parameters according to an embodiment of the present application. As shown in fig. 3, the method includes:

starting a system;

the exposure control module 2 writes initial exposure parameter values into the camera 6;

the image information statistics module 5 acquires image information and performs image preprocessing and information statistics operation;

specifically, the image information statistics module 5 may acquire an original image acquired by the camera 6 based on the initial exposure parameter value, perform processing operations such as black level correction, dead pixel correction, and image interpolation on the original image of the camera, implement conversion of the original image data into RGB data, and send the RGB data to the gradient calculation module 4.

The gradient calculation module 4 calculates the gray value of each pixel in the corrected image;

specifically, the gradient calculating module 4 may correct the gray values of the pixels in the RGB data to obtain a preset number of corrected images, and obtain the gray values of the pixels in the preset number of corrected images. And the gray values of the pixels in the preset number of corrected images are sent to the gamma fitting module 3.

The gamma fitting module 3 determines a target correction value;

specifically, the gamma fitting module 3 may calculate gradient values of each pixel in the preset number of correction images based on gray values of each pixel in the preset number of correction images, calculate exposure evaluation values of each correction image based on gradient values of each pixel in the preset number of correction images, determine a maximum exposure evaluation value, and determine a correction value of the correction image corresponding to the maximum exposure evaluation value as the target correction value. And sends the target correction value to the exposure control module 2.

The exposure control module 2 calculates a target exposure parameter value and sends the target exposure parameter value to the camera;

specifically, the exposure control module 2 calculates a target exposure parameter value based on the initial exposure parameter value and the target correction value, converts the target exposure parameter value into a register parameter value that can be identified by the camera, and sends the target exposure parameter value converted through the I2C bus to the camera.

Based on the method for determining the exposure parameters provided in the above embodiment, correspondingly, the embodiment of the application further provides a specific implementation mode of the device for determining the exposure parameters. Please refer to the following examples.

Referring first to fig. 4, the apparatus for determining exposure parameters provided in the embodiment of the present application includes the following modules: a processing module 41, a correction module 42 and a determination module 43.

A processing module 41, configured to pre-process the obtained original image to obtain a gray value of each pixel point in the original image,

a correction module 42, configured to correct gray values of each pixel point in the original image by using a preset number of correction values, to obtain exposure evaluation values corresponding to the preset number Zhang Jiaozheng of images respectively,

the determining module 43 is configured to determine a target correction value based on the exposure evaluation values respectively corresponding to the preset number Zhang Jiaozheng of images, where the target correction value is a correction value corresponding to a correction image with the largest exposure evaluation value, and determine a target exposure parameter value based on the current exposure parameter value and the target correction value.

The embodiment of the application provides a device for determining exposure parameters, which is used for correcting an original image obtained by acquisition equipment to obtain gray values of all pixel points in the original image, correcting the gray values of all pixel points in the original image by using a preset number of correction values to obtain exposure evaluation values corresponding to preset number Zhang Jiaozheng of images respectively, determining a target correction value based on the exposure evaluation values corresponding to preset number Zhang Jiaozheng of images respectively, wherein the target correction value is a correction value corresponding to a correction image with the largest exposure evaluation value, and determining a target exposure parameter value based on a current exposure parameter value and the target correction value. The embodiment of the application increases the determination efficiency of the exposure parameter value.

In some embodiments, the correction module 42 is specifically configured to correct the gray values of the pixels in the original image based on a preset number of correction values, obtain the gray values of the pixels in a preset number of corrected images, determine, for any corrected image, a gradient value of each pixel in the corrected image based on the gray values of each pixel in the corrected image, and determine, based on the gradient value of each pixel in the corrected image, an exposure evaluation value of the corrected image, so as to obtain exposure evaluation values corresponding to a preset number Zhang Jiaozheng of images, respectively.

In some embodiments, the gray values of the pixels in the original image are corrected based on the preset number of correction values, so that the gray values of the pixels in the preset number of corrected images satisfy the following relationship:

N＝log(λ(1-δ))

wherein ,for the gradient value of the ith pixel point in the corrected image, the value range [0, 1] is taken]，m _i For the gray value of the ith pixel point in the corrected image, lambda is a first adjustment coefficient for adjusting the gradient value +.>Delta is the gray value threshold value, and the value range is [0,1]。

In some embodiments, the determining, based on the gradient values of the pixels in the corrected image, that the exposure evaluation value of the corrected image satisfies the following relationship:

In some embodiments, the first adjustment factor is adjusted as follows:

acquiring an exposure evaluation measurement value of the arbitrary correction image and the exposure evaluation value,

if the exposure evaluation measurement value is identical to the exposure evaluation value, the first adjustment coefficient is not adjusted,

if the exposure evaluation measurement value is greater than the exposure evaluation value, the first adjustment coefficient is increased based on a difference between the exposure evaluation measurement value and the exposure evaluation value,

and if the exposure evaluation measurement value is smaller than the exposure evaluation value, reducing the first adjustment coefficient based on the difference value between the exposure evaluation measurement value and the exposure evaluation value.

In some embodiments, the second adjustment factor is adjusted as follows:

determining an exposure parameter adjustment value based on the exposure parameter value and the current exposure parameter value,

a preset exposure parameter difference threshold range is acquired,

if the exposure parameter adjustment value is greater than the maximum threshold value of the exposure parameter difference threshold range, reducing a second adjustment coefficient of the exposure function,

and if the exposure parameter adjustment value is smaller than the minimum threshold value of the exposure parameter difference threshold value range, reducing the second adjustment coefficient of the exposure function.

In some embodiments, the processing module 41 is specifically configured to pre-process an original image, obtain an RGB image of the original image,

and determining gray values of color channels of pixels in the acquired image based on the RGB image.

Fig. 5 shows a schematic hardware structure of a computing device according to an embodiment of the present application.

A processor 501 and a memory 502 storing computer program instructions may be included in a computing device.

In particular, the processor 501 may include a Central Processing Unit (CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present application.

Memory 502 may include mass storage for data or instructions. By way of example, and not limitation, memory 502 may comprise a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing. Memory 502 may include removable or non-removable (or fixed) media, where appropriate. Memory 502 may be internal or external to the integrated gateway disaster recovery device, where appropriate. In a particular embodiment, the memory 502 is a non-volatile solid state memory.

The memory may include Read Only Memory (ROM), random Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described with reference to methods in accordance with aspects of the present disclosure.

The processor 501 implements the method of determining any one of the exposure parameters in the above-described embodiments by reading and executing the computer program instructions stored in the memory 502.

In one example, the computing device may also include a communication interface 503 and a bus 510. As shown in fig. 5, the processor 501, the memory 502, and the communication interface 503 are connected to each other by a bus 510 and perform communication with each other.

The communication interface 503 is mainly used to implement communication between each module, apparatus, unit and/or device in the embodiments of the present application.

Bus 510 includes hardware, software, or both that couple the components of the online data flow billing device to each other. By way of example, and not limitation, the buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a micro channel architecture (MCa) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of the above. Bus 510 may include one or more buses, where appropriate. Although embodiments of the application have been described and illustrated with respect to a particular bus, embodiments of the application contemplate any suitable bus or interconnect.

The computing device may perform the method for determining exposure parameters in the embodiment of the present application, thereby implementing the method for determining exposure parameters described in connection with fig. 1 and 3.

In addition, in combination with the method for determining the exposure parameters in the above embodiment, the embodiment of the present application may be implemented by providing a computer storage medium. The computer storage medium has stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement a method of determining an exposure parameter of any of the above embodiments.

It should be understood that the embodiments of the application are not limited to the particular arrangements and processes described above and illustrated in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the embodiments of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps, after appreciating the spirit of the embodiments of the present application.

The functional blocks shown in the above-described structural block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of an embodiment of the application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer networks such as the internet, intranets, etc.

It should also be noted that the exemplary embodiments mentioned in the embodiments of the present application describe some methods or systems based on a series of steps or apparatuses. However, the embodiment of the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiment, may be different from the order in the embodiment, or several steps may be performed simultaneously.

Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In the foregoing, only the specific implementation manner of the embodiment of the present application is described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the system, module and unit described above may refer to the corresponding process in the foregoing method embodiment, which is not repeated herein. It should be understood that the scope of the embodiments of the present application is not limited thereto, and any person skilled in the art can easily think of various equivalent modifications or substitutions within the technical scope of the embodiments of the present application, and these modifications or substitutions are intended to be included in the scope of the embodiments of the present application.

Claims

1. A method for determining exposure parameters, comprising:

2. The method for determining exposure parameters according to claim 1, wherein the correcting the gray values of the pixels in the original image by using the preset number of correction values respectively to obtain the exposure evaluation values corresponding to the preset number of Zhang Jiaozheng images respectively includes:

respectively correcting the gray values of all the pixel points in the original image based on the correction values of the preset quantity to obtain the gray values of all the pixel points of the correction images of the preset quantity,

for any correction image, determining the gradient value of each pixel point in the correction image based on the gray value of each pixel point of any correction image,

and determining exposure evaluation values of the corrected image based on the gradient values of all pixel points in the corrected image to obtain exposure evaluation values corresponding to a preset number of Zhang Jiaozheng images respectively.

3. The method for determining exposure parameters according to claim 2, wherein the gray values of the pixels in the original image are corrected based on a preset number of correction values, respectively, so that the gray values of the pixels in the preset number of corrected images satisfy the following relationship:

4. A method for determining an exposure parameter according to claim 2 or 3, wherein the determining, based on the gray value of each pixel of the any one of the corrected images, determines that the gradient value of each pixel in the corrected image satisfies the following relationship:

N＝log(λ(1-δ))

5. The method according to any one of claims 2 to 4, wherein the determination of the exposure evaluation value of the corrected image based on the gradient value of each pixel point in the corrected image satisfies the following relationship:

6. The method of determining exposure parameters according to claim 4, wherein the first adjustment coefficient is adjusted as follows:

acquiring an exposure evaluation measurement value of the any one of the corrected images measured by the exposure evaluation measurement device and the exposure evaluation value,

if the exposure evaluation measurement value is larger than the exposure evaluation value, the first adjustment coefficient is increased based on a difference value between the exposure evaluation measurement value and the exposure evaluation value,

7. The method of determining an exposure parameter according to claim 1, wherein the determining a target exposure parameter value based on a current exposure parameter value and the target correction value satisfies the following relationship:

wherein ,E_t+1 For the target exposure parameter value, alpha is a preset constant, K _p For the second adjustment coefficient,for the target exposure parameter value, E _t Is the current exposure parameter value.

8. The method of determining an exposure parameter according to claim 7, wherein the second adjustment coefficient is adjusted as follows:

determining an exposure parameter adjustment value based on the target exposure parameter value and the current exposure parameter value,

a preset exposure parameter difference threshold range is acquired,

the second adjustment coefficient is adjusted based on the exposure parameter adjustment value and the exposure parameter difference threshold range.

9. The method for determining an exposure parameter according to claim 1, wherein preprocessing the obtained original image to obtain a gray value of each pixel point in the original image comprises:

preprocessing an original image to obtain an RGB image of the original image,

10. An exposure parameter determining apparatus, comprising: