Attention mechanism-based image blind deblurring method and system

Abstract

The invention provides an attention mechanism-based image blind deblurring method and system, and the method comprises the steps that a multi-scale attention network directly recovers a clear image inan end-to-end mode, wherein the multi-scale attention network adopts an asymmetric encoding and decoding structure, and the encoding side of the encoding and decoding structure adopts a residual dense network block to complete feature extraction and expression of an input image by the multi-scale attention network; a plurality of attention modules are arranged on the decoding side of the encodingand decoding structure, the attention modules output preliminary restored images, and the preliminary restored images form a pyramid-type multi-scale structure of the image; the attention module further outputs an attention feature map, and the attention feature map models the relationship between the long-distance areas from the global perspective to process the blurred image; dark channel priorloss and multi-scale content loss form a loss function, and the loss function is used for reversely optimizing the network and is not self-optimized.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an attention mechanism-based blind image deblurring method and system. Background technique [0002] Dynamic scene blur is a common phenomenon caused by factors such as the shaking of the shooting device, the movement of the target object at different depths of field, and the camera being out of focus during the image acquisition process. Blurred images not only affect the visual effect, but also are not conducive to subsequent computer vision tasks such as target detection and semantic segmentation. Therefore, deblurring has always been a basic but very important problem in the field of image processing. [0003] Usually blurred images are mathematically modeled as: [0004] [0005] in, Represents a two-dimensional spatial convolution operation. Blurred Image I Blur is defined by the clear image I Sharp Convolved with the blur kernel K, and then superimposed n...

AI Technical Summary

Problems solved by technology

[0010] The purpose of the present invention is to provide a blind image deblurring method and system based on the attention mechanism, so as to solve the problem that the existing blind deblurring method based on the convolutional neural network cannot efficiently deal with the blurring of complex dynamic scenes

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