CN113628133A - Rain and fog removing method and device based on video image - Google Patents
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Abstract
The invention provides a method and a device for removing rain and fog based on a video image. The method comprises the following steps: acquiring a video to be defogged, and extracting a corresponding image frame of the defogged video from the video to be defogged; constructing a rain and fog separation algorithm, and acquiring a corresponding rain and fog range from a foggy video image frame through the rain and fog separation algorithm; separating a reflection image from the foggy video image frame according to the rain and fog range to be used as an image to be processed; and processing the image to be processed by a contrast stretching method, acquiring the processed image and combining the processed image into a rain and fog removing video. According to the invention, the corresponding rain and fog range can be obtained from the video image frame with rain and fog by constructing a rain and fog separation algorithm, so that rain and fog are accurately separated from the video image frame with rain and fog, the overall contrast of the processed video image frame is improved by a contrast stretching mode, and the defogging efficiency of the whole video processing is improved.
Description
Technical Field
The invention relates to the technical field of computer software, in particular to a method and a device for removing rain and fog based on video images.
Background
Fogging video sharpness is an important issue in the field of computer vision. Under the condition of fog, due to the fact that visibility of a scene is reduced, characteristics such as target contrast and color in a video frame are attenuated, and therefore the requirement that an outdoor video working system needs to accurately extract image characteristics cannot be met. Therefore, how to automatically and real-timely eliminate the influence of fog on scene targets in video frames has important theoretical research significance and practical application value.
At present, most of video image defogging methods have certain problems, the technology is not mature enough, and when defogging is performed on a video image, the defogging speed is slow and the effect is not good because the calculation amount is large, so that a video image-based defogging method and a video image-based defogging device are urgently needed, and the video defogging efficiency can be improved.
The above-described contents are only for assisting understanding of technical aspects of the present invention, and do not represent an admission that the above-described contents are prior art.
Disclosure of Invention
In view of this, the invention provides a method and a device for removing rain and fog based on a video image, and aims to solve the technical problem that in the prior art, rain and fog cannot be processed through a video image frame, so that the rain and fog removing efficiency of the video image is improved.
The technical scheme of the invention is realized as follows:
in one aspect, the invention provides a method for removing rain and fog based on a video image, which comprises the following steps:
s1, acquiring a video to be defogged, and extracting a corresponding image frame of the foggy video from the video to be defogged;
s2, constructing a rain and fog separation algorithm, and acquiring a corresponding rain and fog range from the foggy video image frame through the rain and fog separation algorithm;
s3, separating the reflection image from the foggy video image frame according to the rain and fog range as the image to be processed;
and S4, processing the image to be processed by a contrast stretching method, acquiring the processed image and combining the processed image into a rain and fog removing video.
On the basis of the above technical solution, preferably, in step S1, a video to be defogged is obtained, and a corresponding image frame of the foggy video is extracted from the video to be defogged, and the method further includes the steps of obtaining the video to be defogged, obtaining each corresponding frame of image from the video to be defogged, numbering each frame of image, and dividing the image frame into a foggy video image frame and a fogless video image frame.
On the basis of the above technical solution, preferably, the method further includes the following steps of, in step S2, constructing a rain and fog separation algorithm, and acquiring a corresponding rain and fog range from the foggy video image frame through the rain and fog separation algorithm, and further includes the following steps of constructing the rain and fog separation algorithm, performing convolution operation on the rain and fog separation algorithm and the foggy video image frame, acquiring a luminance component image corresponding to the foggy video image frame, calculating an average value of the luminance component image, and acquiring the corresponding rain and fog range according to the average value.
On the basis of the above technical solution, preferably, the method further includes the following steps:
wherein,
represents the luminance component image, I (x, y) represents the atmospheric scattering model, F (x, y) represents the rain-fog separation algorithm, k represents the normalization constant, and δ represents the standard deviation.
Based on the above technical solution, preferably, in step S3, the method further includes the steps of marking the rain and fog range in the foggy video image frame, converting the foggy video image frame with the mark into a color space, extracting a luminance component of the foggy video image frame with the mark from the color space, obtaining a rain and fog mask according to the luminance component, removing the rain and fog mask from the foggy video image frame with the mark, obtaining a defogged video image frame, obtaining a reflection image from the defogged video image frame through index transformation, and using the reflection image as the image to be processed.
On the basis of the above technical solution, preferably, in step S4, the image to be processed is processed by a contrast stretching method to obtain a processed image and combined into a defogged video, and the method further includes the steps of performing image enhancement and stretching on the image to be processed by the contrast stretching method to obtain a processed image, and recombining the processed image and the fog-free video image frame according to the processed image number to obtain a combined video as the defogged video.
On the basis of the above technical solution, preferably, after the processed image and the fog-free video image frame are recombined to obtain a combined video as a fog-and-rain removing video, the method further includes the steps of comparing the fog-and-rain removing video with a video to be defogged to find out a similar fog-containing video image frame, performing the fog removing process on the fog-containing video image frame again, and placing the fog-containing video image frame after the reprocessing into the fog-and-rain removing video according to the number.
Still further preferably, the video-image-based defogging device includes:
the extracting module is used for acquiring a video to be defogged and extracting a corresponding image frame of the fogging video from the video to be defogged;
the construction module is used for constructing a rain and fog separation algorithm and acquiring a corresponding rain and fog range from the foggy video image frame through the rain and fog separation algorithm;
the separation module is used for separating a reflection image from the foggy video image frame according to the rain and fog range to be used as an image to be processed;
and the combination module is used for processing the image to be processed by a contrast stretching method, acquiring the processed image and combining the processed image into a rain and fog removing video.
In a second aspect, the method for defogging based on a video image further comprises an apparatus comprising: a memory, a processor and a video image based defogging method program stored on the memory and executable on the processor, the video image based defogging method program configured to implement the steps of the video image based defogging method as described above.
In a third aspect, the method for removing rain and fog based on video images further includes a medium, which is a computer medium, and a program of the method for removing rain and fog based on video images is stored on the computer medium, and when the program of the method for removing rain and fog based on video images is executed by a processor, the steps of the method for removing rain and fog based on video images are implemented.
Compared with the prior art, the method for removing the rain and fog based on the video image has the following beneficial effects:
(1) by constructing the rain and fog separation algorithm, the rain and fog range can be accurately divided from the foggy video image frame, so that the subsequent defogging operation on the image frame is facilitated, and the rain and fog removal efficiency of the video image is improved.
(2) The rain and fog removing video image frame is processed through a contrast stretching method, and the overall contrast of the rain and fog removing video image frame can be improved, so that the overall efficiency of subsequent defogging videos is improved, and the user experience is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without any creative effort.
FIG. 1 is a schematic diagram of an apparatus in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of a method for removing rain and fog based on video images according to the present invention;
fig. 3 is a functional block diagram of a first embodiment of a method for removing rain and fog based on video images according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
As shown in fig. 1, the apparatus may include: a processor 1001 such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or may be a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the device, and that in actual implementations the device may include more or less components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a medium, may include therein an operating system, a network communication module, a user interface module, and a video image-based defogging method program.
In the device shown in fig. 1, the network interface 1004 is mainly used to establish a communication connection of the device with a server that stores all data required in the video image-based rain and fog removing method system; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 of the video image-based rain and fog removing method device of the invention can be arranged in the video image-based rain and fog removing method device, and the video image-based rain and fog removing method device calls the video image-based rain and fog removing method program stored in the memory 1005 through the processor 1001 and executes the video image-based rain and fog removing method provided by the invention.
Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of a method for removing rain and fog based on video images according to the present invention.
In this embodiment, the method for removing rain and fog based on a video image includes the following steps:
s10: and acquiring a video to be defogged, and extracting a corresponding image frame of the defogged video from the video to be defogged.
It should be understood that in this embodiment, a to-be-defogged video is obtained first, and each corresponding frame of image is obtained from the to-be-defogged video, and each frame of image is numbered and divided into a fog-video image frame and a fog-free video image frame.
It should be understood that the video to be defogged is generally a video with rain fog, and the defogging process is required to be performed on the video to be defogged because the video shooting effect is not ideal due to the existence of rain fog, and the subsequent processing of the video by workers is affected.
It should be understood that numbering the video image frames facilitates subsequent recombination of the video image frames to form a complete defogged video, and due to the existence of the numbering, problems in video playing cannot be caused, and user experience can be improved.
S20: and constructing a rain and fog separation algorithm, and acquiring a corresponding rain and fog range from the foggy video image frame through the rain and fog separation algorithm.
It should be understood that the system will then construct a rain and fog separation algorithm, perform a convolution operation on the rain and fog separation algorithm and the foggy video image frame to obtain a luminance component image corresponding to the foggy video image frame, calculate an average value of the luminance component image, and obtain a corresponding rain and fog range according to the average value.
It should be understood that, in particular, the rain and fog separation algorithm is:
wherein,
represents the luminance component image, I (x, y) represents the atmospheric scattering model, F (x, y) represents the rain-fog separation algorithm, k represents the normalization constant, and δ represents the standard deviation.
S30: and separating the reflected image from the foggy video image frame according to the rain and fog range to be used as an image to be processed.
It should be understood that the system will mark the rain and fog range in the foggy video image frame, convert the foggy video image frame with the mark into a color space, extract the brightness component of the foggy video image frame with the mark from the color space, obtain a rain and fog mask according to the brightness component, remove the rain and fog mask from the foggy video image frame with the mark, obtain a defogged video image frame, obtain a reflection image from the defogged video image frame through exponential transformation, and use the reflection image as an image to be processed.
S40: and processing the image to be processed by a contrast stretching method, acquiring the processed image and combining the processed image into a rain and fog removing video.
It should be understood that, finally, the system performs image enhancement and stretching on the image to be processed by a contrast stretching method, acquires the processed image, and recombines the processed image and the fog-free video image frame according to the processed image number, and acquires the combined video as the rain and fog removing video.
It should be understood that the system then compares the defogged video with the video to be defogged, finds a similar foggy video image frame, re-defoggs the foggy video image frame, and places the re-processed foggy video image frame into the defogged video according to the number.
The above description is only an example, and does not limit the technical solution of the present application.
As can be easily found from the above description, in the present embodiment, by acquiring a video to be defogged, a corresponding image frame of a foggy video is extracted from the video to be defogged; constructing a rain and fog separation algorithm, and acquiring a corresponding rain and fog range from the foggy video image frame through the rain and fog separation algorithm; separating a reflection image from the foggy video image frame according to the rain and fog range to be used as an image to be processed; and processing the image to be processed by a contrast stretching method, acquiring the processed image and combining the processed image into a rain and fog removing video. The embodiment can obtain the corresponding rain and fog range from the rain and fog video image frames by constructing a rain and fog separation algorithm, so that rain and fog are accurately separated from the rain and fog video image frames, the overall contrast of the processed video image frames is improved by a contrast stretching mode, and the defogging efficiency of the whole video processing is improved.
In addition, the embodiment of the invention also provides a rain and fog removing device based on the video image. As shown in fig. 3, the video image-based defogging device includes: an extraction module 10, a construction module 20, a separation module 30 and a combination module 40.
The extracting module 10 is configured to obtain a video to be defogged, and extract a corresponding video image frame with fog from the video to be defogged;
the construction module 20 is configured to construct a rain and fog separation algorithm, and obtain a corresponding rain and fog range from a foggy video image frame through the rain and fog separation algorithm;
a separation module 30, configured to separate a reflection image from the foggy video image frame according to the rain and fog range, and use the reflection image as an image to be processed;
and the combination module 40 is used for processing the image to be processed by a contrast stretching method, acquiring the processed image and combining the processed image into a rain and fog removing video.
In addition, it should be noted that the above-described embodiments of the apparatus are merely illustrative, and do not limit the scope of the present invention, and in practical applications, a person skilled in the art may select some or all of the modules to implement the purpose of the embodiments according to actual needs, and the present invention is not limited herein.
In addition, the technical details that are not described in detail in this embodiment may be referred to a method for removing rain and fog based on a video image provided in any embodiment of the present invention, and are not described herein again.
Furthermore, an embodiment of the present invention further provides a medium, where the medium is a computer medium, and the computer medium stores a video image-based defogging method program, and the video image-based defogging method program, when executed by a processor, implements the following operations:
s1, acquiring a video to be defogged, and extracting a corresponding image frame of the foggy video from the video to be defogged;
s2, constructing a rain and fog separation algorithm, and acquiring a corresponding rain and fog range from the foggy video image frame through the rain and fog separation algorithm;
s3, separating the reflection image from the foggy video image frame according to the rain and fog range as the image to be processed;
and S4, processing the image to be processed by a contrast stretching method, acquiring the processed image and combining the processed image into a rain and fog removing video.
Further, when executed by the processor, the video image-based defogging method further comprises the following operations:
and acquiring a video to be defogged, acquiring corresponding images of each frame from the video to be defogged, numbering the images of each frame, and dividing the images into a fog video image frame and a fog-free video image frame.
Further, when executed by the processor, the video image-based defogging method further comprises the following operations:
and constructing a rain and fog separation algorithm, performing convolution operation on the rain and fog separation algorithm and the foggy video image frame to obtain a brightness component image corresponding to the foggy video image frame, calculating the average value of the brightness component image, and obtaining a corresponding rain and fog range according to the average value.
Further, when executed by the processor, the video image-based defogging method further comprises the following operations:
the rain and fog separation algorithm comprises the following steps:
wherein,
represents the luminance component image, I (x, y) represents the atmospheric scattering model, F (x, y) represents the rain-fog separation algorithm, k represents the normalization constant, and δ represents the standard deviation.
Further, when executed by the processor, the video image-based defogging method further comprises the following operations:
marking the rain fog range in the foggy video image frame, converting the foggy video image frame with the mark into a color space, extracting the brightness component of the foggy video image frame with the mark from the color space, acquiring a rain fog mask according to the brightness component, removing the rain fog mask from the foggy video image frame with the mark, acquiring a defogging video image frame, converting the defogging video image frame into a reflection image through an index, and taking the reflection image as an image to be processed.
Further, when executed by the processor, the video image-based defogging method further comprises the following operations:
and performing image enhancement and stretching on the image to be processed by a contrast stretching method to obtain the processed image, recombining the processed image and the fog-free video image frame according to the processed image number, and obtaining the combined video as the rain and fog removing video.
Further, when executed by the processor, the video image-based defogging method further comprises the following operations:
and comparing the rain and fog removing video with the to-be-defogged video, finding out similar foggy video image frames, carrying out defogging treatment on the foggy video image frames again, and putting the reprocessed foggy video image frames into the rain and fog removing video according to the serial numbers.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A method for removing rain and fog based on video images is characterized in that: comprises the following steps;
s1, acquiring a video to be defogged, and extracting a corresponding image frame of the foggy video from the video to be defogged;
s2, constructing a rain and fog separation algorithm, and acquiring a corresponding rain and fog range from the foggy video image frame through the rain and fog separation algorithm;
s3, separating the reflection image from the foggy video image frame according to the rain and fog range as the image to be processed;
and S4, processing the image to be processed by a contrast stretching method, acquiring the processed image and combining the processed image into a rain and fog removing video.
2. The video-image-based defogging method according to claim 1, wherein: in step S1, a video to be defogged is obtained, and a corresponding image frame of the fogging video is extracted from the video to be defogged, and the method further includes the steps of obtaining the video to be defogged, obtaining each corresponding frame of image from the video to be defogged, numbering each frame of image, and dividing the image frame into an image frame of the fogging video and an image frame of the non-fogging video.
3. The video-image-based defogging method according to claim 2, wherein: in step S2, a rain and fog separation algorithm is constructed, and a corresponding rain and fog range is obtained from the foggy video image frame through the rain and fog separation algorithm, and the method further includes the following steps of constructing a rain and fog separation algorithm, performing convolution operation on the rain and fog separation algorithm and the foggy video image frame, obtaining a luminance component image corresponding to the foggy video image frame, calculating an average value of the luminance component image, and obtaining the corresponding rain and fog range according to the average value.
4. The video-image-based defogging method according to claim 3, wherein: the rain and fog separation algorithm further comprises the following steps:
wherein,
represents the luminance component image, I (x, y) represents the atmospheric scattering model, F (x, y) represents the rain-fog separation algorithm, k represents the normalization constant, and δ represents the standard deviation.
5. The video-image-based defogging method according to claim 4, wherein: in step S3, the method further includes the steps of marking the rain and fog range in the foggy video image frame, converting the foggy video image frame with the mark into a color space, extracting a luminance component of the foggy video image frame with the mark from the color space, obtaining a rain and fog mask according to the luminance component, removing the rain and fog mask from the foggy video image frame with the mark, obtaining a defogged video image frame, obtaining a reflection image by performing index transformation on the defogged video image frame, and taking the reflection image as the image to be processed.
6. The video-image-based defogging method according to claim 5, wherein: and step S4, processing the image to be processed by a contrast stretching method to obtain the processed image and combine the processed image into a rain and fog removing video, and the method also comprises the following steps of enhancing and stretching the image to be processed by the contrast stretching method to obtain the processed image, recombining the processed image and the fog-free video image frame according to the processed image number to obtain the combined video as the rain and fog removing video.
7. The video-image-based defogging method according to claim 6, wherein: and after the processed image and the fog-free video image frame are recombined to obtain a combined video as a rain and fog removing video, the method further comprises the following steps of comparing the rain and fog removing video with the video to be defogged to find out a similar foggy video image frame, carrying out defogging processing on the foggy video image frame again, and putting the reprocessed foggy video image frame into the rain and fog removing video according to the number.
8. A video-image-based defogging device, comprising:
the extracting module is used for acquiring a video to be defogged and extracting a corresponding image frame of the fogging video from the video to be defogged;
the construction module is used for constructing a rain and fog separation algorithm and acquiring a corresponding rain and fog range from the foggy video image frame through the rain and fog separation algorithm;
the separation module is used for separating a reflection image from the foggy video image frame according to the rain and fog range to be used as an image to be processed;
and the combination module is used for processing the image to be processed by a contrast stretching method, acquiring the processed image and combining the processed image into a rain and fog removing video.
9. An apparatus, characterized in that the apparatus comprises: a memory, a processor and a video image based defogging method program stored on the memory and executable on the processor, the video image based defogging method program configured to implement the steps of the video image based defogging method according to any one of claims 1 to 7.
10. A medium, characterized in that the medium is a computer medium having stored thereon a video-image-based defogging method program which, when executed by a processor, implements the steps of the video-image-based defogging method according to any one of claims 1 to 7.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101754032A (en) * | 2008-12-12 | 2010-06-23 | 汉王科技股份有限公司 | Defogging method capable of keeping colors |
| CN101783012A (en) * | 2010-04-06 | 2010-07-21 | 中南大学 | Automatic image defogging method based on dark primary colour |
| KR101279374B1 (en) * | 2012-11-27 | 2013-07-04 | 주식회사 카이넥스엠 | Fog reduction image enhancer and method for compensating for video of cctv camera |
| CN103218778A (en) * | 2013-03-22 | 2013-07-24 | 华为技术有限公司 | Image and video processing method and device |
| CN103903230A (en) * | 2014-03-28 | 2014-07-02 | 哈尔滨工程大学 | Video image sea fog removal and clearing method |
| CN105303532A (en) * | 2015-10-21 | 2016-02-03 | 北京工业大学 | Wavelet domain Retinex image defogging method |
| CN106296612A (en) * | 2016-08-09 | 2017-01-04 | 南京工业大学 | Hierarchical monitoring video sharpening system and method for image quality evaluation and weather condition guidance |
| CN106548463A (en) * | 2016-10-28 | 2017-03-29 | 大连理工大学 | Based on dark and the sea fog image automatic defogging method and system of Retinex |
| CN107767353A (en) * | 2017-12-04 | 2018-03-06 | 河南工业大学 | A kind of adapting to image defogging method based on definition evaluation |
| CN108093175A (en) * | 2017-12-25 | 2018-05-29 | 北京航空航天大学 | A kind of adaptive defogging method of real-time high-definition video and device |
| US20200027203A1 (en) * | 2018-07-20 | 2020-01-23 | Baidu Online Network Technology (Beijing) Co., Ltd. | Method and apparatus for processing image |
| CN110930326A (en) * | 2019-11-15 | 2020-03-27 | 浙江大华技术股份有限公司 | Image and video defogging method and related device |
-
2021
- 2021-07-28 CN CN202110855465.5A patent/CN113628133A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101754032A (en) * | 2008-12-12 | 2010-06-23 | 汉王科技股份有限公司 | Defogging method capable of keeping colors |
| CN101783012A (en) * | 2010-04-06 | 2010-07-21 | 中南大学 | Automatic image defogging method based on dark primary colour |
| KR101279374B1 (en) * | 2012-11-27 | 2013-07-04 | 주식회사 카이넥스엠 | Fog reduction image enhancer and method for compensating for video of cctv camera |
| CN103218778A (en) * | 2013-03-22 | 2013-07-24 | 华为技术有限公司 | Image and video processing method and device |
| CN103903230A (en) * | 2014-03-28 | 2014-07-02 | 哈尔滨工程大学 | Video image sea fog removal and clearing method |
| CN105303532A (en) * | 2015-10-21 | 2016-02-03 | 北京工业大学 | Wavelet domain Retinex image defogging method |
| CN106296612A (en) * | 2016-08-09 | 2017-01-04 | 南京工业大学 | Hierarchical monitoring video sharpening system and method for image quality evaluation and weather condition guidance |
| CN106548463A (en) * | 2016-10-28 | 2017-03-29 | 大连理工大学 | Based on dark and the sea fog image automatic defogging method and system of Retinex |
| CN107767353A (en) * | 2017-12-04 | 2018-03-06 | 河南工业大学 | A kind of adapting to image defogging method based on definition evaluation |
| CN108093175A (en) * | 2017-12-25 | 2018-05-29 | 北京航空航天大学 | A kind of adaptive defogging method of real-time high-definition video and device |
| US20200027203A1 (en) * | 2018-07-20 | 2020-01-23 | Baidu Online Network Technology (Beijing) Co., Ltd. | Method and apparatus for processing image |
| CN110930326A (en) * | 2019-11-15 | 2020-03-27 | 浙江大华技术股份有限公司 | Image and video defogging method and related device |
Non-Patent Citations (1)
| Title |
|---|
| 谢斌 等: "基于雾气遮罩理论的图像去雾算法", 计算机工程与科学, no. 06, pages 1 - 3 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115034999A (en) * | 2022-07-06 | 2022-09-09 | 四川大学 | Image rain removing method based on rain and fog separation processing and multi-scale network |
| CN115034999B (en) * | 2022-07-06 | 2024-03-19 | 四川大学 | Image rain removing method based on rain and fog separation processing and multi-scale network |
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