Fix motion blur by integrating the high frequency for edge and low frequency for structure with MCMS
Fix motion blur by integrating the high frequency for edge and low frequency for structure with MCMS
MCMS: Multi-Category Information and Multi-Scale Stripe Attention for Blind Motion Deblurring
arXiv paper abstract https://arxiv.org/abs/2405.01083
arXiv PDF paper https://arxiv.org/pdf/2405.01083
… A blind motion deblurring network (MCMS) based on multi-category information and multi-scale stripe attention mechanism is proposed … a three-stage encoder-decoder model
… first stage … extracting the features of the high-frequency … second stage … extracting the features of the low-frequency … third stage integrates … low-frequency … features … high-frequency … features, and the original blurred image … to recover the final clear image.
… model effectively improves motion deblurring by fusing the edge information of the high-frequency component and the structural information of the low-frequency component.
In addition, a grouped feature fusion technique is developed so as to achieve richer, more three-dimensional and comprehensive utilization of various types of features at a deep level.
Next, a multi-scale stripe attention mechanism (MSSA) … combines the anisotropy and multi-scale information … enhances the capability of the deep model in feature representation.
Large-scale comparative studies on various datasets show that the strategy in this paper works better than the recently published measures.
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