Depth Separable Convolution Lightweight Blind Motion Deblurring Algorithm

2022 Proceedings of WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications   unpublished
Aiming at the motion blur problem caused by handheld camera shake and object movement in the process of photo acquisition, an image deblur algorithm based on depth separable convolution lightweight generative adversarial network was proposed. Firstly, a depth separable convolution residual block with selfattention mechanism is introduced in the generator. Secondly, Transpose convolution module is replaced by the Pixel-Shuffle up-sampling module. Finally, The combination of perceptual loss and
more » ... lativistic generative adversarial loss can effectively alleviates the mode collapse problem of traditional GAN and improves the stability of model training. Experimental results show that compared with Deblur-GAN the number of parameters of the proposed algorithm is significantly reduced, the deblurring time of a single image is reduced by 50%, the deblurring image is clearer in subjective vision, and the objective evaluation indexes of image quality such as peak signal-to-noise ratio and structural similarity are also significantly improved.
doi:10.18178/wcse.2022.04.057 fatcat:wf6sn6iiijcrblzcwazlh7euym