As a common weather condition,rainy weather can have a certain impact on computer vision,causing rain streaks and blurred details in images.Therefore,an efficient single image rain removal algorithm is needed to improve image quality.Most existing rain removal algorithms only focus on removing rain streaks,while neglecting the restoration of detailed information in the image afterremoval.In order to better detect rain streaks,a shallow feature extraction module and a deep feature extraction module is proposed.In the shallow extraction module,the residual dense block is selected,while in the deep extraction module,two dual-attention modules and two convolution layers are selected as residual groups composed of residual blocks.In order to restore image detail information,a multi-scale detail restoration module containing global and local branches is proposed.Numerous experiments on both synthetic and real datasets have shown that the proposed algorithm achieves PSNR and SSIM of 40.41 dB and 0.989 respectively,while preserving image details.