To restore background details while removing different rain patterns,an image rain re-moval method based on attention mechanism and multi-scale feature fusion is proposed.The net-work adopts a two-branch structure,which is used for rain stripe removal and background recovery respectively.The rain-stripe extraction module uses a multi-scale attention mechanism of cross-space learning to help improve the image quality in the rain-stripe removal task and improve the rain removal effect through multi-scale context information capture,mean calculation,weight calcu-lation and overall information synthesis.The background recovery module includes multi-scale fea-ture extraction part and feature fusion part,and adopts multiple extended convolution layers,each with different expansion factors,to enlarge the receptive field and extract multi-scale image back-ground features.Large nuclear convolution is used to fuse and adjust the extracted multi-scale fea-ture information,so as to recover the background more accurately.The experimental results on sev-eral public data sets show that the proposed method can effectively remove the rain lines in the real rain image scene,and can better recover the details of the image background.
维普
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