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14 February 2020 Blind deblurring with image layer separation using relative smoothness
Shikang Wu, Hanyu Hong, Yu Shi, Xia Hua
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Proceedings Volume 11431, MIPPR 2019: Parallel Processing of Images and Optimization Techniques; and Medical Imaging; 1143103 (2020) https://doi.org/10.1117/12.2538072
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China
Abstract
Blind image deblurring is a challenging problem which has drawn a lot of attention in recent years. Previous work states shows that image details caused by blur could adversely affect the kernel estimation, especially when the blur kernel is large. In this paper, we focus on how to extract the suitable salient structure for kernel estimation from a single blurred image. A fast method for estimating the salient structure of an image is proposed in the paper. The image is divided into two layers with different smoothness, and the local relative smoothness layer eliminates the image structure that adversely affects the kernel estimation. Further kernel estimation using the layer can obtain more accurate results. Substantial experiment shows that our method is effective on some challenging examples.
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Shikang Wu, Hanyu Hong, Yu Shi, and Xia Hua "Blind deblurring with image layer separation using relative smoothness", Proc. SPIE 11431, MIPPR 2019: Parallel Processing of Images and Optimization Techniques; and Medical Imaging, 1143103 (14 February 2020); https://doi.org/10.1117/12.2538072
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KEYWORDS
Image analysis
Image restoration
Computer vision technology
Deconvolution
Image processing
Machine vision
Visualization
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