Aggregating Local and Global Features via Selective State Spaces Model for Efficient Image Deblurring

arXiv:2403.20106v1 Announce Type: cross
Abstract: Image deblurring is a process of restoring a high quality image from the corresponding blurred image. Significant progress in this field has been made possible by the emergence of various effective deep learning models, including CNNs and Transformers. However, these methods often face the dilemma between eliminating long-range blur degradation perturbations and maintaining computational efficiency, which hinders their practical application. To address this issue, we propose an efficient image deblurring network that leverages selective structured …

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