WO2022213372A1 - Procédé et appareil de débrumage d'image, dispositif électronique et support lisible par ordinateur - Google Patents

Procédé et appareil de débrumage d'image, dispositif électronique et support lisible par ordinateur Download PDF

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WO2022213372A1
WO2022213372A1 PCT/CN2021/086221 CN2021086221W WO2022213372A1 WO 2022213372 A1 WO2022213372 A1 WO 2022213372A1 CN 2021086221 W CN2021086221 W CN 2021086221W WO 2022213372 A1 WO2022213372 A1 WO 2022213372A1
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parameter
function
target
image
piecewise
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PCT/CN2021/086221
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English (en)
Chinese (zh)
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伦朝林
卢庆博
丁蕾
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深圳市大疆创新科技有限公司
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Priority to PCT/CN2021/086221 priority Critical patent/WO2022213372A1/fr
Publication of WO2022213372A1 publication Critical patent/WO2022213372A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/73—Deblurring; Sharpening
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/90—Dynamic range modification of images or parts thereof
    • G06T5/94—Dynamic range modification of images or parts thereof based on local image properties, e.g. for local contrast enhancement

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  • the embodiments of the present application relate to the field of computer technologies, and in particular, to an image defogging method, apparatus, electronic device, and computer-readable medium.
  • the images and videos taken usually have poor image quality and low definition.
  • the image is usually dehazed by a dark channel dehazing algorithm.
  • the dark channel dehazing algorithm uses a single linear function to brighten the pixels larger than a certain value in a fixed way, and directly adjust the pixels smaller than a certain value to zero, which is prone to overexposure of bright details and loss of dark details in the image. situation, resulting in poor image quality.
  • the embodiments of the present application propose an image defogging method, apparatus, electronic device, and computer-readable medium, so as to solve the technical problem of poor image quality after the image is defogged in the prior art.
  • an embodiment of the present application provides an image dehazing method, including: acquiring fog intensity information of an image to be processed; based on the fog intensity information, a preset parameter set in a fog-free scene and a fog-free scene Determine the target parameter set based on the target parameter set; determine the target mapping function based on the target parameter set, and perform dehazing processing on the to-be-processed image based on the target mapping function to obtain the target image after dehazing, wherein,
  • the target mapping function is a continuous function including a plurality of piecewise functions.
  • an image defogging device including: an acquisition unit configured to acquire fog intensity information of an image to be processed; a determination unit configured to, based on the fog intensity information, preset The parameter set in the fog-free scene and the parameter set in the dense fog scene determine a target parameter set; the processing unit is configured to determine a target mapping function based on the target parameter set, and based on the target mapping function The image is dehazed to obtain a target image after dehazing, wherein the target mapping function is a continuous function including a plurality of piecewise functions.
  • embodiments of the present application provide an electronic device, including: a processor and a memory; a memory for storing program instructions; a processor for executing program instructions stored in the memory, and when the program instructions are executed, processing
  • the device is configured to perform the following steps: obtaining fog intensity information of the image to be processed; determining a target parameter set based on the fog intensity information, a preset parameter set in a fog-free scene and a parameter set in a dense fog scene; based on the target
  • the parameter set determines a target mapping function, and based on the target mapping function, the image to be processed is subjected to dehazing processing to obtain a target image after dehazing, wherein the target mapping function is a multi-segment function. Continuous function.
  • an embodiment of the present application provides a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, implements the method described in the first aspect.
  • the embodiments of the present application provide an image dehazing method, device, electronic device, and computer-readable medium, by acquiring fog intensity information of an image to be processed, and then based on the fog intensity information, a preset parameter set in a fog-free scene and a dense fog
  • the parameter set in the fog scene is determined
  • the target parameter set is determined
  • the target mapping function is determined based on the target parameter set, so that the image to be processed can be dehazed based on the target mapping function, and the target image after dehazing can be obtained.
  • the target mapping function is a continuous function including multiple piecewise functions, different piecewise functions can be used to process pixel values in different numerical ranges, avoiding the overexposure of bright details in the image due to the use of a single linear function. As well as a large loss of details in the shadows, the quality of the image is improved.
  • FIG. 1 is a flowchart of an embodiment of an image dehazing method according to the present application.
  • Fig. 2 is according to the graph of the target mapping function in the image dehazing method of the present application
  • FIG. 3 is a schematic structural diagram of an embodiment of an image defogging device according to the present application.
  • FIG. 4 is a schematic structural diagram of an embodiment of an electronic device according to the present application.
  • FIG. 1 shows a flowchart of an image dehazing method according to the present application.
  • the image dehazing method of the present application can be run on various electronic devices, which may include but are not limited to: servers, smart phones, tablet computers, laptop computers, vehicle-mounted computers, desktop computers, set-top boxes, wearable devices, etc. Wait.
  • the process of the image dehazing method includes the following steps:
  • Step 101 Obtain fog intensity information of the image to be processed.
  • the execution body of the image defogging method may first acquire the image to be processed.
  • the image to be processed can be captured by the above-mentioned executive body through the image acquisition device (such as a camera) installed in it, or can be stored locally in advance (such as stored in a local album), or can be obtained by the above-mentioned executive body from the Internet or other devices.
  • the image to be processed may be an image to be dehazed.
  • the above-mentioned execution body may acquire the fog intensity information of the to-be-processed image.
  • the fog intensity information can be used to indicate the fog intensity of the image, which can be a value in a preset value interval, such as a value in [0,1]. The stronger the fog, the higher the value.
  • the fog intensity information of the image to be processed can be preset by a technician, and the above-mentioned execution body can directly read it in this case.
  • the execution subject may query current weather conditions to determine fog intensity information based on the weather conditions.
  • the above-mentioned execution body can automatically detect the fog intensity of the image to be processed to obtain fog intensity information.
  • the image to be processed may be input into a pre-trained neural network for fog intensity detection to obtain a fog intensity detection result.
  • the neural network can be trained using a large number of samples and supervised learning.
  • the method for obtaining the fog intensity information may also be set to other settings as required, and is not limited to the above-mentioned ones.
  • Step 102 Determine the target parameter set based on the fog intensity information, the preset parameter set in the fog-free scene, and the parameter set in the dense fog scene.
  • a parameter set in a fog-free scene and a parameter set in a dense fog scene may be preset in the above-mentioned execution body.
  • the parameter set in the fog-free scene and the parameter set in the dense fog scene can respectively contain multiple parameters and correspond one-to-one.
  • the parameters in the two parameter sets are the parameters of the preset mapping function.
  • the mapping function can be used to characterize the correspondence between the pixel values before dehazing and the pixel values after dehazing. That is, after inputting the pixel value of a certain pixel in the image before the defogging process into the mapping function, the pixel value of the pixel after the defogging process can be obtained.
  • the mapping function is a continuous function containing multiple piecewise functions.
  • the parameters of the mapping function can be adjusted for the fog-free scene and the dense fog scene in advance to obtain the parameter set in the fog-free scene and the parameter set in the dense fog scene.
  • the image quality of the fog-free image can be compared with different parameters, and the parameters used to obtain the best image quality can be summarized into the fog-free scene. parameter set.
  • the image quality after dehazing the dense fog image with different parameters can be compared, and the parameters used to obtain the best image quality can be summarized into the dense fog scene. parameter set.
  • the above-mentioned execution subject may determine the target parameter set based on the fog intensity information, the preset parameter set in the fog-free scene, and the parameter set in the dense fog scene.
  • the target parameter set is the parameter set applicable to the current fog intensity.
  • the above-mentioned executive body may perform interpolation on the preset parameter set in the fog-free scene and the parameter set in the dense fog scene based on the fog intensity information to obtain the target parameter set.
  • the parameter set in the fog-free scene includes x 0 ', x 1 ', x 2 ', y 1 ', y 2 '
  • the parameter set in the dense fog scene includes x 0 ', x 1 '', x 2 ”, y 1 ”, y 2 ”
  • the interpolation method may adopt various interpolation methods such as linear interpolation and nonlinear interpolation, which are not limited here. Taking the interpolation of x 1 ' and x 1 ' as an example, if the fog intensity information is represented as M, then x 1 can be x 1 '+M(x 1 ''-x 1 ').
  • Step 103 Determine a target mapping function based on the target parameter set, and perform dehazing processing on the image to be processed based on the target mapping function to obtain a target image after dehazing.
  • a preset mapping function may be stored in the above-mentioned execution body.
  • a mapping function is a continuous function containing multiple piecewise functions, which contain multiple parameters. Depending on the fog intensity, the parameters used by the mapping function can be different.
  • the above-mentioned execution body may use a preset mapping function using target parameters as the target mapping function, and thus, the target mapping function is also a continuous function including a plurality of segment functions.
  • the above-mentioned execution body may perform dehazing processing on the to-be-processed image based on the target mapping function to obtain the target image after dehazing.
  • each piecewise function may correspond to a pixel value interval.
  • the above-mentioned execution body may determine a piecewise function for processing the pixel according to the pixel value of the pixel, so as to input the pixel value into the piecewise function to obtain the pixel The new pixel value of the point. After performing the above operations on all pixels, the target image after dehazing can be obtained.
  • the target mapping function may include a first piecewise function.
  • the target parameter set may include a first parameter (which can be marked as x 0 ), the first parameter is a positive number smaller than the target value, and the target value is determined based on the ambient light brightness value (which can be marked as A) and the transmittance (which can be marked as t) .
  • the ambient light brightness value and transmittance are commonly used parameters in the dark channel dehazing algorithm, and will not be described here.
  • the above-mentioned execution body may adjust the pixel values in the image to be processed that are less than or equal to the first parameter based on the first piecewise function.
  • the first piecewise function may be a constant (eg, 0), and the target value may be A(1-t), where 0 ⁇ x 0 ⁇ A(1-t). If a certain pixel value of the image to be processed is less than x 0 , the pixel value can be adjusted to a constant (eg, 0).
  • the conventional dark channel dehazing algorithm usually directly adjusts the pixel value less than A(1-t) to 0, the conventional dark channel dehazing algorithm is prone to the loss of a large number of dark details in the image. In this implementation manner, since x 0 ⁇ A(1-t), fewer pixel values are adjusted to 0, so that more dark details are protected, thereby improving the image quality after dehazing.
  • the target mapping function may further include a second piecewise function.
  • the second piecewise function may be a monotonically increasing function (eg, a monotonically increasing linear function or a monotonically increasing nonlinear function).
  • the target parameter set also includes a second parameter (may be denoted as x 1 ), and the second parameter may be greater than the first parameter (x 0 ) and smaller than the ambient light brightness value A, ie A(1-t) ⁇ x 1 ⁇ A.
  • the above-mentioned execution body may adjust the pixel value (denoted as x) in the image to be processed that is larger than the first parameter and smaller than the second parameter based on the second piecewise function. That is, when x 0 ⁇ x ⁇ x 1 , use the second piecewise function to adjust x to obtain the adjusted pixel value (denoted as y).
  • the target parameter set further includes a third parameter (which may be denoted as y 1 ), and the third parameter is a positive number smaller than the ambient light brightness value A, that is, y 1 ⁇ A.
  • the second piecewise function may be a linear function, and the slope of the second piecewise function is determined based on the first parameter, the second parameter and the third parameter.
  • the second piecewise function can be:
  • the conventional dark channel dehazing algorithm usually directly adjusts the pixel value less than A(1-t) to 0, the conventional dark channel dehazing algorithm is prone to the loss of a large number of dark details in the image.
  • x 0 ⁇ A(1-t) the pixel values in the range of (x 0 , A(1-t)) are all adjusted to a number greater than 0, so that fewer pixel values are adjusted to 0, so that more dark details are protected, thereby improving the image quality after dehazing.
  • the target mapping function further includes a third piecewise function
  • the third piecewise function may be a monotonically increasing function (such as a monotonically increasing linear function or a monotonically increasing nonlinear function) .
  • the above-mentioned execution body may adjust the pixel value (may be denoted as x) in the image to be processed that is greater than or equal to the second parameter x 1 and less than or equal to the ambient light brightness value A based on the third piecewise function. That is, if x 1 ⁇ x ⁇ A, use the third piecewise function to adjust x to obtain the adjusted pixel value (denoted as y).
  • the third piecewise function may be a linear function, and the slope of the third piecewise function may be determined based on the transmittance, such as directly using the slope 1/t of the mapping function in the conventional dark channel dehazing algorithm, at this time , the second piecewise function can be:
  • the target mapping function further includes a fourth piecewise function
  • the fourth piecewise function is a monotonically increasing function (eg, a monotonically increasing linear function or a monotonically increasing nonlinear function).
  • the above-mentioned execution body may adjust the pixel value (which may be denoted as x) in the image to be processed that is greater than the ambient light brightness value A based on the fourth piecewise function. That is, if x>A, use the fourth piecewise function to adjust x to obtain the adjusted pixel value (denoted as y).
  • the target parameter set further includes a fifth parameter (denoted as x 2 ) and a sixth parameter (denoted as y 2 ).
  • the fifth parameter is greater than the ambient light brightness value A and smaller than the maximum pixel value (eg, 255).
  • the six parameter is less than or equal to the maximum pixel value (eg 255). That is, A ⁇ x 2 ⁇ 255, and y 2 ⁇ 255.
  • the fourth piecewise function may be a linear function, and the slope of the fourth piecewise function may be smaller than the slope (eg, 1/t) adopted by the conventional dark channel dehazing algorithm. Specifically, the slope of the fourth piecewise function may be determined based on the fifth parameter, the sixth parameter and the ambient light brightness value, and the fourth piecewise function may be:
  • the conventional dark channel dehazing algorithm usually directly adjusts the pixel value x greater than A to A+(x-A)/t, it is easy to adjust the pixel value greater than A to the maximum value of 255, resulting in overexposure of bright details in the image.
  • the slope of the fourth piecewise function is less than 1/t, for pixel values greater than A, the adjusted value can be reduced, so that more bright details can be protected, thereby further improving the dehazing process. post image quality.
  • FIG. 2 shows a graph of an object mapping function in an image dehazing method according to the present application.
  • the graph of the target mapping function includes four parts, corresponding to the first piecewise function, the second piecewise function, the third piecewise function and the fourth piecewise function respectively.
  • the horizontal axis represents the original pixel value
  • the vertical axis represents the pixel value after dehazing.
  • the target mapping function is as follows:
  • the target mapping function may also use other functional forms that can achieve similar functions, such as multi-segment linear mapping functions, smooth curve functions, etc., which are not specifically limited in this embodiment of the present application.
  • the fog intensity information of the image to be processed is obtained, and then the target parameter set is determined based on the fog intensity information, a preset parameter set in a fog-free scene, and a parameter set in a dense fog scene , and then determine the target mapping function based on the target parameter set, so that the image to be processed can be dehazed based on the target mapping function, and the target image after dehazing can be obtained.
  • the target mapping function is a continuous function including multiple piecewise functions, different piecewise functions can be used to process pixel values in different numerical ranges, avoiding the overexposure of bright details in the image due to the use of a single linear function. As well as a large loss of details in the shadows, the quality of the image is improved.
  • the present application provides an embodiment of an image defogging apparatus, and the apparatus embodiment corresponds to the method embodiment shown in FIG. 1 .
  • the electronic device can be among various electronic devices.
  • the above-mentioned image defogging apparatus 300 in this embodiment includes: an acquiring unit 301 configured to acquire fog intensity information of an image to be processed; a determining unit 302 configured to, based on the above fog intensity information, a preset The parameter set in the fog-free scene and the parameter set in the dense fog scene determine the target parameter set; the processing unit 303 is configured to determine the target mapping function based on the above target parameter set, and based on the above target mapping function. Dehazing is performed to obtain a target image after dehazing, wherein the target mapping function is a continuous function including a plurality of piecewise functions.
  • the target mapping function includes a first piecewise function, the first piecewise function is a constant, the target parameter set includes a first parameter, and the first parameter is smaller than the target value
  • the above-mentioned target value is determined based on the brightness value of the ambient light and the transmittance; the above-mentioned processing unit is further configured to: based on the above-mentioned first piecewise function, the pixel values in the above-mentioned to-be-processed image that are less than or equal to the above-mentioned first parameter are processed. Adjustment.
  • the foregoing first piecewise function is a constant.
  • the target mapping function further includes a second piecewise function, the second piecewise function is a monotonically increasing function, the target parameter set further includes a second parameter, and the second parameter Greater than the first parameter and less than the ambient light brightness value;
  • the processing unit is further configured to: based on the second piecewise function, the pixel values in the to-be-processed image that are greater than the first parameter and less than the second parameter are processed. Adjustment.
  • the target parameter set further includes a third parameter, and the third parameter is a positive number smaller than the ambient light brightness value; the second piecewise function is a linear function, and the third parameter is a linear function.
  • the slope of the bipartite function is determined based on the aforementioned first parameter, the aforementioned second parameter, and the aforementioned third parameter.
  • the above-mentioned target mapping function further includes a third piecewise function, and the above-mentioned third piecewise function is a monotonically increasing function; the above-mentioned processing unit is further configured to: based on the above-mentioned third The piecewise function adjusts pixel values in the image to be processed that are greater than or equal to the second parameter and less than or equal to the ambient light brightness value.
  • the third piecewise function is a linear function, and the slope of the third piecewise function is determined based on the transmittance.
  • the above-mentioned target mapping function further includes a fourth piecewise function, and the above-mentioned fourth piecewise function is a monotonically increasing function; the above-mentioned processing unit is further configured to: based on the above-mentioned fourth The piecewise function adjusts pixel values in the image to be processed that are greater than the ambient light brightness value.
  • the target parameter set further includes a fifth parameter and a sixth parameter, the fifth parameter is greater than the ambient light brightness value and less than the maximum pixel value, and the sixth parameter is less than or equal to The above-mentioned maximum pixel value; the above-mentioned fourth piecewise function is a linear function, and the slope of the above-mentioned fourth piecewise function is determined based on the above-mentioned fifth parameter, the above-mentioned sixth parameter and the above-mentioned ambient light brightness value.
  • the above determining unit is further configured to: perform interpolation on a preset parameter set in a fog-free scene and a parameter set in a dense fog scene based on the above fog intensity information, Get the target parameter set.
  • the image defogging device obtained by the above-mentioned embodiments of the present application obtains the fog intensity information of the image to be processed, and then determines the fog intensity information based on the fog intensity information, the preset parameter set in the fog-free scene and the parameter set in the dense fog scene.
  • a target parameter set, and then a target mapping function is determined based on the target parameter set, so that the image to be processed can be dehazed based on the target mapping function, and a dehazed target image can be obtained.
  • the target mapping function is a continuous function including multiple piecewise functions, different piecewise functions can be used to process pixel values in different numerical ranges, avoiding the overexposure of bright details in the image due to the use of a single linear function. As well as a large loss of details in the shadows, the quality of the image is improved.
  • the present application provides an embodiment of an electronic device, which corresponds to the method embodiment shown in Fig. 1 .
  • the electronic device may include: a processor 401 and a memory 402 .
  • the above-mentioned memory 401 can be used to store program instructions.
  • the above-mentioned processor 402 can be used to execute the program instructions stored in the above-mentioned memory.
  • the above-mentioned processor can be used to perform the following steps: obtaining fog intensity information of the image to be processed; The parameter set in the fog-free scene and the parameter set in the dense fog scene are determined, and the target parameter set is determined; the target mapping function is determined based on the above target parameter set, and the image to be processed is dehazed based on the above target mapping function.
  • the target mapping function includes a first piecewise function, the first piecewise function is a constant, the target parameter set includes a first parameter, and the first parameter is smaller than the target value
  • the above-mentioned target value is determined based on the ambient light brightness value and transmittance; the above-mentioned processor is further configured to perform the following steps: based on the above-mentioned first piecewise function, the pixel value in the above-mentioned to-be-processed image that is less than or equal to the above-mentioned first parameter is determined. make adjustments.
  • the foregoing first piecewise function is a constant.
  • the target mapping function further includes a second piecewise function, the second piecewise function is a monotonically increasing function, the target parameter set further includes a second parameter, and the second parameter greater than the first parameter and less than the ambient light brightness value;
  • the processor is further configured to perform the following steps: based on the second piecewise function, the pixel value in the image to be processed that is greater than the first parameter and less than the second parameter is analyzed. make adjustments.
  • the target parameter set further includes a third parameter, and the third parameter is a positive number smaller than the ambient light brightness value; the second piecewise function is a linear function, and the third parameter is a linear function.
  • the slope of the bipartite function is determined based on the aforementioned first parameter, the aforementioned second parameter, and the aforementioned third parameter.
  • the above-mentioned target mapping function further includes a third piecewise function, and the above-mentioned third piecewise function is a monotonically increasing function; the above-mentioned processor is further configured to perform the following steps: based on the above-mentioned first The three-piece function adjusts the pixel values in the image to be processed that are greater than or equal to the second parameter and less than or equal to the ambient light brightness value.
  • the third piecewise function is a linear function, and the slope of the third piecewise function is determined based on the transmittance.
  • the above-mentioned target mapping function further includes a fourth piecewise function, and the above-mentioned fourth piecewise function is a monotonically increasing function; the above-mentioned processor is further configured to perform the following steps: based on the above-mentioned first The four-segment function adjusts the pixel values in the image to be processed that are greater than the ambient light brightness value.
  • the target parameter set further includes a fifth parameter and a sixth parameter, the fifth parameter is greater than the ambient light brightness value and less than the maximum pixel value, and the sixth parameter is less than or equal to The above-mentioned maximum pixel value; the above-mentioned fourth piecewise function is a linear function, and the slope of the above-mentioned fourth piecewise function is determined based on the above-mentioned fifth parameter, the above-mentioned sixth parameter and the above-mentioned ambient light brightness value.
  • the above-mentioned processor is further configured to perform the following steps: based on the above-mentioned fog intensity information, perform interpolation on a preset parameter set in a fog-free scene and a parameter set in a dense fog scene , get the target parameter set.
  • the electronic device obtained by the above-mentioned embodiments of the present application obtains the fog intensity information of the image to be processed, and then determines the target based on the fog intensity information, the preset parameter set in the fog-free scene and the parameter set in the dense fog scene parameter set, and then determine the target mapping function based on the target parameter set, so that the image to be processed can be dehazed based on the target mapping function, and the target image after dehazing can be obtained.
  • the target mapping function is a continuous function including multiple piecewise functions, different piecewise functions can be used to process pixel values in different numerical ranges, avoiding the overexposure of bright details in the image due to the use of a single linear function. As well as a large loss of details in the shadows, the quality of the image is improved.
  • an electronic device can be either a processing chip or a processing unit in the device, or a product, such as a camera, a mobile phone, or a camera-equipped gimbal, drone, or unmanned vehicle.
  • a processing chip or a processing unit in the device or a product, such as a camera, a mobile phone, or a camera-equipped gimbal, drone, or unmanned vehicle.
  • the electronic device is not specifically limited here.
  • the description is relatively simple, and for related parts, please refer to the partial description of the method embodiment.
  • Embodiments of the present application further provide a computer-readable medium, where a computer program is stored on the computer-readable medium.
  • a computer program is stored on the computer-readable medium.
  • the computer program is executed by a processor, each process of the above-mentioned embodiments of the image dehazing method can be achieved, and the same technology can be achieved. Effect.
  • the computer program is executed by the processor, each process of the embodiments of the above-mentioned methods is implemented, which will not be repeated here.
  • the embodiments of the present application may be provided as a method, an apparatus, or a computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-readable media having computer-usable program code embodied therein, including but not limited to disk storage, CD-ROM, optical storage, and the like.
  • These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing terminal equipment to operate in a particular manner, such that the instructions stored in the computer readable memory result in an article of manufacture comprising instruction means, the The instruction means implement the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

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Abstract

Sont divulgués dans les modes de réalisation de la présente demande un procédé et un appareil de débrumage d'image, ainsi qu'un dispositif électronique et un support lisible par ordinateur. Le procédé comprend : l'acquisition d'informations d'intensité de voile d'une image à traiter ; la détermination d'un ensemble de paramètres cibles sur la base des informations d'intensité de voile, d'un ensemble de paramètres prédéfini dans un scénario sans voile, et d'un ensemble de paramètres dans un scénario de voile dense ; et la détermination d'une fonction de mappage cible sur la base de l'ensemble de paramètres cibles, et la mise en œuvre, sur la base de la fonction de mappage cible, d'un traitement de débrumage sur l'image à traiter, de façon à obtenir une image cible débrumée, la fonction de mappage cible étant une fonction continue comprenant de multiples fonctions par morceaux. Au moyen de la mise en œuvre, la qualité d'image après le traitement de débrumage est améliorée.
PCT/CN2021/086221 2021-04-09 2021-04-09 Procédé et appareil de débrumage d'image, dispositif électronique et support lisible par ordinateur WO2022213372A1 (fr)

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