Two-stage image rain removal method and system based on residual adversarial refinement network

Abstract

The invention discloses an image rain removal method based on a residual adversarial refinement network, which can effectively remove raindrops in an image and restore a real scene image. According tothe method, rain removal is divided into two stages, in the first stage, a residual image is removed from an original image, a clear image is recovered, the recovered image is input into the second stage, background information of the part shielded by raindrops is recovered, the image is refined, and the quality is improved. According to the method, a rain image is regarded as synthesis of a clear image and a residual image, based on the principle, the residual image is obtained from an original rain image through a residual network, and the residual image is subtracted from the original image to obtain an output image of a first stage; in the second stage, the generative adversarial network is adopted to take the output image and the residual image in the first stage as input, the residual image is taken as an attention mechanism, and the network is assisted to recover a more real image. The invention further provides an image rain removing system.

Description

technical field [0001] The present invention relates to the technical fields of computer vision, deep learning and generative confrontational neural network, specifically a two-stage image deraining method and system based on residual confrontation refinement network, implicit rain model and its application in image processing Applications. Background technique [0002] Rain is a common weather phenomenon, but its presence may greatly affect the visibility of objects and scenes, especially in the case of heavy rain, the accumulation of rainwater from all directions makes the objects and scenes in the image become Indistinct. Images and videos captured in the rain are not only greatly affected at the level of human vision, but also for computer vision systems, it interferes and degrades the performance of many computer vision and image processing tasks, such as object detection and target tracking, Drone-based video surveillance, autonomous driving and driver assistance, an...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the problem that the rainwater image modeling method in the prior art is not suitable for real rainwater images, and the real rainwater images are often much more complex than the simulated data modeled, and there are also problems of blurring and distortion after domain conversion and heavy rain image processing , a two-stage deraining method based on residual adversarial refinement network is proposed

Images