Single image rain removing method based on optimization algorithm in combination with residual network

An optimization algorithm, a single image technology, applied in the field of computer vision, can solve problems such as poor rain track recognition effect

Inactive Publication Date: 2019-08-09
DALIAN UNIV OF TECH
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Problems solved by technology

This method is effective for some examples of rain traces, but not all raindrops have the same angle, proportion and density, so it is very poor for some specific rain traces.

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  • Single image rain removing method based on optimization algorithm in combination with residual network
  • Single image rain removing method based on optimization algorithm in combination with residual network
  • Single image rain removing method based on optimization algorithm in combination with residual network

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Embodiment Construction

[0044] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific examples. These examples are illustrative only and not limiting of the invention.

[0045] The present invention proposes a kind of image deraining method based on residual network and admm algorithm, the concrete implementation steps of this method: at first be training residual network, this algorithm is set to the depth of convolutional neural network as 26, uses weight decay (weightdecay ) is 10 -10 , the SGD algorithm with a momentum of 0.9 is used for training, and the size of each training block (batch) is 30. The learning rate is initialized to 0.0001, attenuated by 0.1 every 10,000 rounds of training, and a total of 100,000 rounds of training were performed. In this algorithm, the size of the filter is set as s1=s2=s3=3, a1=a2=16, which are al...

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Abstract

The invention discloses a single image rain removing method based on an optimization algorithm in combination with a residual network, and belongs to the technical field of computer vision application. The method comprises: using an alternating direction multiplier method ADMM for solving a rainy day image imaging model, embedding a residual error network and a noise reduction algorithm into an ADMM framework to serve as background priori and rain priori for iteration, and dividing an image shot in rainy days into a rain-free clear background part and a rain trace part. In the residual network, a synthetic rain map/clear background image pair is used as a training set for training to describe image background priori. Experimental verification proves that the PSNR value of the rain removalresult of the ADMM algorithm embedded with the residual error network is higher than that of other rain removal algorithms. In addition, other existing rain removing algorithms are embedded into the ADMM rain removing algorithm to serve as background prior iteration, and the obtained rain removing effect is superior to the effect of an original algorithm.

Description

technical field [0001] The invention relates to the field of computer vision, and relates to a method for removing rain from a single image based on an optimization algorithm combined with a residual network. Background technique [0002] In rainy days, the impact of rain marks on images and videos is often undesirable, and rain marks will seriously affect the performance of many outdoor computer vision applications, such as surveillance systems and automatic driving systems. Raindrops falling or flowing down from the camera lens will block, distort and blur the image, and long-distance raindrops falling continuously from the camera lens will also reduce visibility. The principle of affecting visibility is similar to that of fog on image visibility. , the light is scattered by the water in the air, creating a veiled effect. Many computer vision applications such as image enhancement and tracking require an effective method for deraining images. However, when the structure ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06N3/04
CPCG06T5/003G06T5/002G06T2207/10016G06T2207/20081G06N3/045
Inventor 薛昕惟刘日升王祎樊鑫
Owner DALIAN UNIV OF TECH
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