CN108093175A - A kind of adaptive defogging method of real-time high-definition video and device - Google Patents
A kind of adaptive defogging method of real-time high-definition video and device Download PDFInfo
- Publication number
- CN108093175A CN108093175A CN201711419404.4A CN201711419404A CN108093175A CN 108093175 A CN108093175 A CN 108093175A CN 201711419404 A CN201711419404 A CN 201711419404A CN 108093175 A CN108093175 A CN 108093175A
- Authority
- CN
- China
- Prior art keywords
- image
- defogging
- video
- real
- chip
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/10—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
- H04N23/81—Camera processing pipelines; Components thereof for suppressing or minimising disturbance in the image signal generation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/70—SSIS architectures; Circuits associated therewith
- H04N25/71—Charge-coupled device [CCD] sensors; Charge-transfer registers specially adapted for CCD sensors
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/64—Circuits for processing colour signals
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Image Processing (AREA)
Abstract
The present invention relates to a kind of adaptive defogging method of real-time high-definition video and device, which includes video image acquisition module, video image defogging processing module, communication interface module, encoding video pictures and display module；Video image acquisition module realizes the acquisition and decoding of vision signal, the defogging processing of video image defogging processing modules implement vision signal, communication interface module realization device is exchanged with the instruction of host computer, and encoding video pictures realize the coding output and display of video with display module.This method be according to high-definition image data volume it is big the characteristics of, assumed using rational, it is proposed that the method for estimation of a kind of smaller transmissivity of calculation amount and air light intensity；Calculation amount is greatly reduced while defog effect is improved, ensures the real-time of defogging algorithm, while makes image more smooth, more naturally.The configuration of the present invention is simple, it is easy to accomplish, can defogging intensity be selected according to the concentration self-adapting of mist, haze, more intelligent and hommization.
Description
Technical Field
The invention relates to a real-time high-definition video self-adaptive defogging method and a device, which can be used for verifying various defogging methods including a real-time high-definition video self-adaptive defogging algorithm; the method can realize a real-time self-adaptive defogging function for the high-definition video, can remarkably improve the acquisition and observation effects of the video, and belongs to the field of video/image processing and computer vision.
Background
With the development of computer vision systems and their application in the fields of military affairs, traffic and safety monitoring, image defogging has become an important research direction for computer vision. The image of gathering can be by serious degradation because of the effect of atmosphere scattering under the bad weather of fog, haze and so on, makes the image colour be grey white partially, and the contrast reduces, and the object characteristic is difficult to discern, not only makes the visual effect variation, and the image sight reduces, still can influence the processing in image later stage, more can influence all kinds of system work that rely on optical imaging instrument, like satellite remote sensing system, aerial photography system, outdoor control and target identification system etc..
Defogging devices have been widely used in practice. However, the existing defogging device can only achieve real-time defogging of a standard definition video, or cannot meet the requirement of real-time performance at all, or cannot meet the self-adaptive selection of defogging intensity. In order to solve the series of problems, the invention designs a real-time high-definition video self-adaptive defogging device and a real-time high-definition video self-adaptive defogging method.
The real-time high-definition video self-adaptive defogging method still adopts the idea of calculating the image transmittance and the atmospheric light intensity frame by frame, but for the requirement of real-time property, the atmospheric light intensity and the transmittance calculated by the previous frame of image are adopted to approximate the atmospheric light intensity and the transmittance of the current frame of image. By utilizing the parallel computing characteristic of the FPGA and designing a parallel computing method, the running speed of a computational defogging algorithm is increased, and the real-time performance can be ensured under a high-definition video;
the research of the defogging method is one of the hot spots in the field of machine vision at present, and attracts the attention of a plurality of domestic and foreign research institutions; in 2009, a Single Image Haze use Dark Channel Prior document published in international top conference CVPR researches a defogging method to obtain a good practical effect, but distortion occurs in processing of a large-area sky fogging Image, which is caused by the fact that a sky area does not meet Dark Channel Prior, and the soft matching method for calculating the transmittance provided by the article can obtain a finer transmittance map, but is complex in calculation and cannot meet the requirement of real-time performance. The method and the device can be adaptive to various natural scenes, automatically select the defogging algorithm strength, and meet the real-time requirement, and are important for realizing the real-time high-definition defogging function, so that the research on the adaptive defogging method and the device for the real-time high-definition video is of great significance.
Chinese patent document No. CN 107071353A discloses an image defogging device. According to the method, a TMS320DM6437 chip is selected as a processor, a TVP5150 analog-to-digital converter is selected as a decoding chip, only standard-definition image data can be processed, different defogging algorithms can be selected for fog images with different intensities only through a manual selection method, and the defogging algorithms cannot be selected in a self-adaptive mode.
Chinese patent publication No. CN 107194894A discloses a video defogging method and system. According to the method, a defogging method based on the Dark Channel Prior is adopted, so that effective defogging of the monitoring video can be realized, but the instantaneity cannot be guaranteed.
Disclosure of Invention
The invention solves the problems: the method and the device overcome the defects of the prior art and provide the real-time high-definition video self-adaptive defogging method and the device so as to solve the problems of degraded quality, blurred image, poor image visual effect and the like of the image extracted by the existing real-time camera system.
The technical scheme adopted by the invention is as follows: the invention discloses an image defogging device which comprises a video image acquisition module, a video image defogging processing module, a communication interface module and a video image coding and display module.
The video image acquisition module comprises a video signal receiving device and a video decoding chip, wherein the video signal receiving device is generally a CCD high-definition camera, and the decoding chip is a GS2971A 3G-SDI video decoding chip.
The video image defogging processing module comprises a processor and an external extension connected with the processor, wherein the processor adopts an XC7K325T FPGA chip, and the external extension is a DDR3, an SRAM, a FLASH, a communication chip and the like connected with the processor.
The communication interface module comprises a communication chip and a communication protocol, wherein the communication chip adopts MAX3077E, and the communication protocol adopts RS422 bus which is mature in industry.
The video image display module comprises a coding chip and a high-definition video image display, wherein the coding chip selects a GS2972 digital-to-analog converter.
The real-time high-definition video self-adaptive defogging method based on the device comprises the following steps:
first, for a pixel point x, the degradation model of an original image J (x) is:
I(x)＝J(x)t(x)+A(1-t(x))
where I (x) represents a foggy image, J (x) represents an original fogless image, t (x) represents transmittance, and A represents atmospheric light intensity. The image degradation degree is related to the distance, and the long-distance degraded image can be seen as that a layer of uniform fog is covered in different local areas on the original clear image, so that the image defogging algorithm usually assumes that the local depth of field of the image is the same, i.e., t (x) is obtained through a local image block, and the atmospheric light intensity A is a constant.
In the second step, the solving process of J (x) at each pixel point can be simplified:
whereinC＝A(1-t(x))。
Thirdly, calculating a dark channel image by using a dark channel first-pass algorithm, and selecting an original image brightness value at a position corresponding to a pixel value with the highest brightness of 0.1% in a dark channel as an estimated value of atmospheric light intensity A;
wherein I dark (x) Representing dark channel images, I c (y) denotes each channel of the color image, Ω (x) denotes the image block centered on pixel x, and c denotes the three color channels r, g, b of the image.Representing the pixel value of 0.1% of the highest brightness in the dark channel, I (x) representing the original input image, a c And A both represent atmospheric light intensity;
fourthly, according to the calculated atmospheric light intensity A, the transmission rate t (x) is estimated according to the formula:
where ω =0.95, in real life there are particles in the air even on a sunny day, and it is therefore necessary to retain a certain degree of mist during defogging, which may introduce a factor ω between [0,1 ].
Fifthly, calculating a gear selection parameter alpha according to the obtained transmissivity t (x),
wherein beta is 1 ，β 2 Representing a threshold value of transmission, alpha 1 ,α 2 ,α 3 For the gear control parameter, | t (x) | | represents the transmittance 1 norm;
sixthly, solving t (x), A and alpha through the calculation, and adopting a parameter suppression algorithm during defogging treatment, wherein the algorithm specifically comprises the following steps:
wherein x represents the position coordinates of a pixel point on an image, I (x) represents a fogged image, t (x) represents the transmittance, t 0 Represents the lower limit of transmittance, J (x) represents the haze-free image to be restored, A represents the intensity of atmospheric light 0 Representing the upper limit of the atmospheric light intensity, wherein the parameter alpha is a defogging gear selection parameter; in order to avoid the problem that when the value of the projection map t (x) is small, the value of J (x) is large, so that the image is white as a whole, a threshold value t is set 0 When the value of t is less than t 0 When, adopt t 0 Performing operation; in order to avoid the problem that when the value of the atmospheric light intensity A is large, it causes the processed image to be discolored and a large amount of color unevenness occurs, a threshold value A is set 0 When A is greater than A 0 When using A 0 And (6) performing operation.
Compared with the prior art, the invention has the characteristics that:
(1) The system is simple to realize, has good real-time performance, and can perform self-adaptive defogging aiming at the fog concentration. Compared with the traditional single Gain/off method, the defogging capacity is improved, and the main reasons are as follows: (1) By adopting a simplified calculation method, the defogging effect can be improved, the calculation amount can be reduced, and the real-time performance of the defogging algorithm can be ensured. (2) Increasing A by adopting a method of over-parameter inhibition 0 And t 0 The calculated atmospheric light intensity and transmittance are subjected to parameter suppression, so that the image is prevented from being distorted by white cast, color spots and the like, and the image is smoother and more natural.
(2) Patent CN102017000379449 proposes a video defogging method and a system thereof, but a hardware system is not used explicitly, so that whether real-time image defogging operation can be realized cannot be judged, and meanwhile, multiple approximate solution methods are used for the same parameter in the patent, so that the solution precision is greatly reduced, and the defogging effect is poor; the defogging method and the defogging device have the advantages that the FPGA is used as the main control chip, the advantages of parallel computing can be fully exerted, a small amount of reasonable approximation is adopted, the operation amount is effectively reduced, the computing precision and the implementation effect can be guaranteed, and the real-time defogging of images with the resolution of 1080P can be realized.
Drawings
FIG. 1 is a flow chart of a real-time high definition video adaptive defogging device according to the present invention;
FIG. 2 is a flow chart of a real-time high definition video adaptive defogging method according to the present invention;
fig. 3 is a simulation test chart of the real-time high-definition video adaptive defogging method and device of the invention, wherein a is a fogging image and b is an image after the defogging operation.
Detailed Description
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
Fig. 1 shows a flow chart of a real-time high-definition video adaptive defogging device according to the present invention, which includes a video image acquisition module, a video image defogging processing module, a communication interface module, and a video image coding and display module.
The video image acquisition module comprises a video signal receiving device and a decoding chip, wherein the video signal receiving device is generally a CCD (charge coupled device) camera, and the decoding chip is a GS2971A SDI (Serial digital interface) signal decoding chip; the specific process is that image data collected by a CCD camera passes through a decoding chip GS2971A, an input serial signal is converted into a parallel digital image code stream, and the decoding chip GS2971A is connected with an XC7K325T chip;
the video image defogging processing module comprises a processor and an external extension connected with the processor, wherein the processor adopts an XC7K325T FPGA chip of Xilinx company, and the external extension is an SRAM, a DDR3, a FLASH, a communication chip and the like connected with the processor; the specific process is that a digital image code stream processed by a decoding chip GS2971A is stored in DDR3, video data is cached, parameters obtained through calculation are stored in SRAM, a program in XC7K325T is stored in an external memory FLASH, the program is loaded from the FLASH every time the power is turned on, and the communication chip realizes the communication between the XC7K325T FPGA chip and an external computer;
the communication interface module comprises a communication chip, wherein the communication chip adopts MAX3077E, and a communication protocol adopts an industrially mature RS422 bus;
the video image display module comprises an encoding chip and a video image display, wherein the encoding chip selects GS2972. The specific process is that the digital image code stream processed by the modules is converted into a serial video signal after being coded by a coding chip GS2972 and is displayed by a video image display;
the above description is the whole process of the real-time high-definition video adaptive defogging device of the present invention, but the implementation process is not intended to limit the present invention, and those skilled in the art may make corresponding modifications without departing from the present invention, and the scope of the present invention is defined by the claims.
Fig. 2 is a flow chart of a real-time high-definition video adaptive defogging method according to the present invention, which includes the following specific steps:
(1) Format conversion is carried out on the input video image, and the YUV422 format is converted into the RGB format, so that subsequent data processing is facilitated;
(2) Calculating the dark channel by using a dark channel first-pass algorithm
(3) Selecting the original image brightness value at the position corresponding to the pixel value with the highest brightness of 0.1% in the dark channel as the estimated value of the atmospheric light intensity A;
the transmittance is estimated by the formula
(4) Calculating a gear selection parameter alpha according to the obtained transmissivity t (x),
wherein beta is 1 ，β 2 Denotes a threshold value of transmittance, α 1 ,α 2 ,α 3 For the gear control parameter, | t (x) | | represents the transmittance 1 norm;
(5) The t (x), A and alpha are obtained through the calculation, and a parameter suppression algorithm is adopted during defogging treatment, and the method specifically comprises the following steps:
wherein x represents the position coordinates of a pixel point on an image, I (x) represents a fogged image, t (x) represents the transmittance, t 0 Denotes the lower limit of transmittance, J (x) denotes a haze-free image to be restored, A denotes atmospheric light intensity, A denotes 0 Representing the upper limit of the atmospheric light intensity, wherein the parameter alpha is a defogging gear selection parameter; in order to avoid the problem that when the value of the projection map t (x) is small, the value of J (x) is large, so that the image is white as a whole, a threshold value t is set 0 When the value of t is less than t 0 When, adopt t 0 Performing operation; in order to avoid the problem that when the value of the atmospheric light intensity A is large, the processed image may be discolored and a large amount of color unevenness may occur, a threshold value A is set 0 When A is greater than A 0 When using A 0 And (6) performing operation.
Fig. 3 is a simulation test chart of the real-time high-definition video adaptive defogging device and method of the present invention, wherein a is a real fogging image shot in the air, and b is an image processed by the defogging device and method of the present invention.
Those matters not described in detail in the present specification are well known in the art to which the skilled person pertains.
The above examples are provided only for the purpose of describing the present invention, and are not intended to limit the scope of the present invention. The scope of the invention is defined by the appended claims. Various equivalent substitutions and modifications can be made without departing from the spirit and principles of the invention, and are intended to be within the scope of the invention.
Claims (7)
1. A real-time high-definition video self-adaptive defogging method is characterized by comprising the following steps: the realization steps are as follows:
(1) The brightness value of the original image corresponding to the pixel value of 0.1% with the highest brightness in the dark channel in the collected image is used as the estimated value of the atmospheric light intensity A, and the estimation formula of the transmissivity t (x) is as follows
Where ω =0.95,x, y represents the coordinates of the position of the pixel point on the image, I c (y) denotes each channel of the color image, Ω (x) denotes the image block centered on pixel x, c denotes the three color channels A of the image, r, g, b c And A both represent atmospheric light intensity;
(2) Calculating a defogging gear selection parameter alpha according to the obtained transmissivity t (x),
wherein beta is 1 ，β 2 Denotes a threshold value of transmittance, α 1 ,α 2 ,α 3 For gear control parameters, | t (x) | tableShowing a transmission 1 norm;
(3) Obtaining a fog-free image J (x) by t (x), A and alpha and adopting an algorithm of parameter suppression during defogging treatment, wherein the formula is
Wherein I (x) represents a fogged image, t 0 Denotes the lower limit of transmittance, J (x) denotes a haze-free image to be restored, A 0 The upper limit of the atmospheric light intensity is shown, and the parameter alpha is a defogging gear selection parameter.
2. The real-time high-definition video adaptive defogging method according to claim 1, wherein: the value of t (x) is small, i.e., t (x)&0.1, the value of J (x) is too large, so that the whole image is too white, and in order to avoid the problem, a threshold value t is set 0 =0.1, when the value of t is less than t 0 When using t 0 Performing operation; when the value of the atmospheric light intensity A is large, namely A&220, which can cause the color cast of the processed image and a great amount of color spots, and a threshold value A is set 0 When A is greater than A 0 When using A 0 And (6) performing operation.
3. The utility model provides a real-time high definition video self-adaptation defogging device which characterized in that: the system comprises a video image acquisition module, a video image defogging processing module, a communication interface module and a video image coding and displaying module; the video image acquisition module comprises a video signal receiving device and a decoding chip, the video image processing module comprises a signal processor and an external expander connected with the signal processor, the communication interface module comprises a main control chip and an external expander connected with the main control chip, and the video image coding and displaying module comprises a coding chip and a video image display.
4. The real-time high-definition video adaptive defogging device according to claim 3, wherein: the video signal receiving device is a CCD camera and realizes a real-time video information acquisition function, the decoding chip selects GS2971A to realize a real-time high-definition video signal decoding function, and decoded image signals are transmitted to the video processing module.
5. The real-time high-definition video self-adaptive defogging device according to claim 3, wherein: the video image processing module comprises a processor and an external extension connected with the processor, wherein the processor adopts an XC7K325T FPGA chip to realize a high-definition video self-adaptive defogging algorithm and defogging gear calculation, the external extension is a DDR3, an SRAM, a FLASH and a communication chip connected with the external extension, the DDR3 and the SRAM are used for caching image data, the FLASH is used for storing program data, and the communication chip is used for interacting a main program with the outside through a serial port.
6. The real-time high-definition video adaptive defogging device according to claim 3, wherein: the video image coding and displaying module comprises a coding chip and a high-definition video image display, wherein the coding chip selects GS2972 and is used for converting parallel image data into serial data so as to be convenient for transmission, and the high-definition video image display only selects a general SDI high-definition video display and is used for displaying processed video in real time.
7. The real-time high-definition video adaptive defogging device according to claim 3, wherein: the communication interface module comprises a communication chip and a communication protocol, wherein the communication chip adopts MAX3077E, and the communication protocol adopts RS422 bus which is mature in industry, so that the communication function of the main program and an external computer is realized.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711419404.4A CN108093175B (en) | 2017-12-25 | 2017-12-25 | A kind of adaptive defogging method of real-time high-definition video and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711419404.4A CN108093175B (en) | 2017-12-25 | 2017-12-25 | A kind of adaptive defogging method of real-time high-definition video and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108093175A true CN108093175A (en) | 2018-05-29 |
| CN108093175B CN108093175B (en) | 2018-11-13 |
Family
ID=62179017
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711419404.4A Active CN108093175B (en) | 2017-12-25 | 2017-12-25 | A kind of adaptive defogging method of real-time high-definition video and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108093175B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109584186A (en) * | 2018-12-25 | 2019-04-05 | 西北工业大学 | A kind of unmanned aerial vehicle onboard image defogging method and device |
| CN110072107A (en) * | 2019-04-25 | 2019-07-30 | 南京理工大学 | A kind of haze video-frequency compression method shared based on estimation |
| CN111866516A (en) * | 2020-06-24 | 2020-10-30 | 北京航空航天大学 | Real-time image enhancement device and method for gray-scale video |
| CN113628133A (en) * | 2021-07-28 | 2021-11-09 | 武汉三江中电科技有限责任公司 | Rain and fog removing method and device based on video image |
| CN114565519A (en) * | 2022-01-13 | 2022-05-31 | 深圳市文立科技有限公司 | Image fog penetration method and device and storage medium |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103079062A (en) * | 2013-02-05 | 2013-05-01 | 武汉科技大学 | Intelligent video surveillance system |
| CN103164845A (en) * | 2011-12-16 | 2013-06-19 | 中国科学院沈阳自动化研究所 | Real-time image mist elimination device and method |
| CN103218778A (en) * | 2013-03-22 | 2013-07-24 | 华为技术有限公司 | Image and video processing method and device |
| CN103347171A (en) * | 2013-06-27 | 2013-10-09 | 河海大学常州校区 | Foggy day video processing system and method based on DSPs |
| CN104008527A (en) * | 2014-04-16 | 2014-08-27 | 南京航空航天大学 | Method for defogging single image |
| CN104732497A (en) * | 2015-03-31 | 2015-06-24 | 北京交通大学 | Image defogging method, FPGA and defogging system including FPGA |
| CN106469440A (en) * | 2016-09-08 | 2017-03-01 | 西安电子科技大学 | Dark mist elimination parallel optimization method based on OpenCL |
| CN106530246A (en) * | 2016-10-28 | 2017-03-22 | 大连理工大学 | Image dehazing method and system based on dark channel and non-local prior |
| CN106548461A (en) * | 2016-10-25 | 2017-03-29 | 湘潭大学 | Image defogging method |
| CN106709901A (en) * | 2016-11-10 | 2017-05-24 | 西安电子科技大学 | Simulation fog image generation method based on depth priori |
| CN106709893A (en) * | 2016-12-28 | 2017-05-24 | 西北大学 | All-time haze image sharpness recovery method |
| CN106780380A (en) * | 2016-12-09 | 2017-05-31 | 电子科技大学 | A kind of image defogging method and system |
| CN106780384A (en) * | 2016-12-15 | 2017-05-31 | 上海交通大学 | A kind of the real-time of cold light source abdominal cavity image parameters self adaptation that be applicable goes smog method |
| CN107194894A (en) * | 2017-05-25 | 2017-09-22 | 河南师范大学 | A kind of video defogging method and its system |
| CN107451966A (en) * | 2017-07-25 | 2017-12-08 | 四川大学 | A kind of real-time video defogging method realized using gray-scale map guiding filtering |
-
2017
- 2017-12-25 CN CN201711419404.4A patent/CN108093175B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103164845A (en) * | 2011-12-16 | 2013-06-19 | 中国科学院沈阳自动化研究所 | Real-time image mist elimination device and method |
| CN103079062A (en) * | 2013-02-05 | 2013-05-01 | 武汉科技大学 | Intelligent video surveillance system |
| CN103218778A (en) * | 2013-03-22 | 2013-07-24 | 华为技术有限公司 | Image and video processing method and device |
| CN103347171A (en) * | 2013-06-27 | 2013-10-09 | 河海大学常州校区 | Foggy day video processing system and method based on DSPs |
| CN104008527A (en) * | 2014-04-16 | 2014-08-27 | 南京航空航天大学 | Method for defogging single image |
| CN104732497A (en) * | 2015-03-31 | 2015-06-24 | 北京交通大学 | Image defogging method, FPGA and defogging system including FPGA |
| CN106469440A (en) * | 2016-09-08 | 2017-03-01 | 西安电子科技大学 | Dark mist elimination parallel optimization method based on OpenCL |
| CN106548461A (en) * | 2016-10-25 | 2017-03-29 | 湘潭大学 | Image defogging method |
| CN106530246A (en) * | 2016-10-28 | 2017-03-22 | 大连理工大学 | Image dehazing method and system based on dark channel and non-local prior |
| CN106709901A (en) * | 2016-11-10 | 2017-05-24 | 西安电子科技大学 | Simulation fog image generation method based on depth priori |
| CN106780380A (en) * | 2016-12-09 | 2017-05-31 | 电子科技大学 | A kind of image defogging method and system |
| CN106780384A (en) * | 2016-12-15 | 2017-05-31 | 上海交通大学 | A kind of the real-time of cold light source abdominal cavity image parameters self adaptation that be applicable goes smog method |
| CN106709893A (en) * | 2016-12-28 | 2017-05-24 | 西北大学 | All-time haze image sharpness recovery method |
| CN107194894A (en) * | 2017-05-25 | 2017-09-22 | 河南师范大学 | A kind of video defogging method and its system |
| CN107451966A (en) * | 2017-07-25 | 2017-12-08 | 四川大学 | A kind of real-time video defogging method realized using gray-scale map guiding filtering |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109584186A (en) * | 2018-12-25 | 2019-04-05 | 西北工业大学 | A kind of unmanned aerial vehicle onboard image defogging method and device |
| CN110072107A (en) * | 2019-04-25 | 2019-07-30 | 南京理工大学 | A kind of haze video-frequency compression method shared based on estimation |
| CN111866516A (en) * | 2020-06-24 | 2020-10-30 | 北京航空航天大学 | Real-time image enhancement device and method for gray-scale video |
| CN111866516B (en) * | 2020-06-24 | 2021-12-17 | 北京航空航天大学 | Real-time image enhancement device and method for gray-scale video |
| CN113628133A (en) * | 2021-07-28 | 2021-11-09 | 武汉三江中电科技有限责任公司 | Rain and fog removing method and device based on video image |
| CN114565519A (en) * | 2022-01-13 | 2022-05-31 | 深圳市文立科技有限公司 | Image fog penetration method and device and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108093175B (en) | 2018-11-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110148095B (en) | Underwater image enhancement method and enhancement device | |
| CN108093175A (en) | A kind of adaptive defogging method of real-time high-definition video and device | |
| CN110619593B (en) | Double-exposure video imaging system based on dynamic scene | |
| CN105631829B (en) | Night haze image defogging method based on dark channel prior and color correction | |
| CN109688382B (en) | Underwater image processing system of underwater robot | |
| CN106897981A (en) | A kind of enhancement method of low-illumination image based on guiding filtering | |
| CN107292830B (en) | Low-illumination image enhancement and evaluation method | |
| CN102750674A (en) | Video image defogging method based on self-adapting allowance | |
| Zheng et al. | Infrared traffic image enhancement algorithm based on dark channel prior and gamma correction | |
| CN110163807B (en) | Low-illumination image enhancement method based on expected bright channel | |
| CN107862672B (en) | Image defogging method and device | |
| CN107958465A (en) | A kind of single image to the fog method based on depth convolutional neural networks | |
| CN108154492B (en) | A kind of image based on non-local mean filtering goes haze method | |
| CN107077830B (en) | Screen brightness adjusting method suitable for unmanned aerial vehicle control end and unmanned aerial vehicle control end | |
| CN110689490A (en) | Underwater image restoration method based on texture color features and optimized transmittance | |
| CN109639994B (en) | Dynamic adjusting method for exposure time of embedded vehicle-mounted camera | |
| CN105989583B (en) | A kind of image defogging method | |
| CN104899836A (en) | Foggy image enhancing device and method based on near infrared multispectral imaging | |
| CN107317967A (en) | Image processing method, device, mobile terminal and computer-readable recording medium | |
| CN103226816A (en) | Haze image medium transmission rate estimation and optimization method based on quick gaussian filtering | |
| CN117197004B (en) | Low-illumination image optimization enhancement method and system | |
| CN109345479B (en) | Real-time preprocessing method and storage medium for video monitoring data | |
| CN107317969A (en) | Image defogging method, device, computer can storage medium and mobile terminals | |
| CN107623831A (en) | A kind of building visual phone imaging device full-color round the clock | |
| CN107277369B (en) | Image processing method, device, computer readable storage medium and computer equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |