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Single image rain removing method and device based on dark channel and fuzzy width learning

A single image and dark channel technology, applied in the field of image processing, can solve the problems that the movement track is easily affected by external factors such as wind, the model establishment and scene restoration are complicated, and the state of raindrop particles is changeable, so as to improve the rainwater removal effect, The effect of reducing network training time and enhancing color reproduction

Active Publication Date: 2019-08-09
SHANGHAI NORMAL UNIVERSITY
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Problems solved by technology

Due to the absorption and scattering of atmospheric light by aerosol particles, the pixel intensity in the image changes relatively slowly
Compared with steady-state bad weather, the particles of dynamic bad weather such as rainy weather are usually much larger, and the trajectory of these particles is easily affected by external factors such as wind while falling rapidly, resulting in blurring and rain in the image. Line occlusion makes model establishment and scene restoration more complicated, causing problems such as overbrightness in local areas and blurred background images
The degradation of image quality in rainy days greatly restricts the functions of outdoor intelligent vision systems such as visual monitoring, visual navigation and target tracking, and the state of raindrop particles is changeable, and the direction and thickness of rain lines are different in different situations

Method used

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  • Single image rain removing method and device based on dark channel and fuzzy width learning
  • Single image rain removing method and device based on dark channel and fuzzy width learning
  • Single image rain removing method and device based on dark channel and fuzzy width learning

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Embodiment Construction

[0038] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is carried out on the premise of the technical solution of the present invention, and detailed implementation and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.

[0039] A single image rain removal processing method based on dark channel and fuzzy width learning, the method is implemented by a computer system in the form of a computer program, the computer system includes a memory, a processor, and a program stored in the memory and executed by the processor programs such as figure 1 As shown, the processor implements the following steps when executing the program:

[0040] Step S1: Dehaze the original image preprocessing,

[0041] Specifically, the dark channel priority dehazing algorithm is used to remove the foggy rain scene in the distanc...

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Abstract

The invention relates to a single image rain removing method and device based on dark channel and fuzzy width learning. The method comprises the steps: S1, carrying out defogging preprocessing on an original image; S2, carrying out high-low frequency separation on the image after defogging pretreatment, taking a high-frequency part to carry out color space conversion, and converting the RGB colorspace into a YCbCr color space; S3, taking the Y channel of the YCbCr color space corresponding to the image of the training set part as the input of fuzzy width learning to carry out model training;S4, taking the Y channel of the test set part as the input of fuzzy width learning to obtain a rain-free graph of the Y channel; S5, combining the high-pass layer rain removal graph with the low-passbase layer to obtain a preliminary rain removal effect graph; and S6, based on the defogged and preprocessed image, carrying out optimization processing on the preliminary rain removal effect pictureto obtain a final rain removal effect picture. Compared with the prior art, the method has the advantages of high color rendition degree and the like.

Description

technical field [0001] The invention relates to image processing technology, in particular to a method and device for removing rain from a single image based on dark channel and fuzzy width learning. Background technique [0002] Computer vision systems are widely used in various industries, including video surveillance, visual tracking and navigation, intelligent transportation, entertainment industry, etc. Computer vision systems in indoor situations have been commonly used and studied, while some outdoor conditions such as rain, snow, and fog are still challenging problems for computer vision systems. Common adverse weather is mainly divided into steady-state adverse weather (mainly refers to fog and haze) and dynamic adverse weather (mainly refers to rain, snow, sandstorm, etc.) according to the composition of particles and visual characteristics. Among them, the steady-state adverse weather is mainly composed of aerosol system composed of very small water droplets and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20081G06T5/77
Inventor 林晓陈万生郑晓妹黄继风盛斌王志杰
Owner SHANGHAI NORMAL UNIVERSITY
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