Name
Abstract | ||
|---|---|---|
This work investigates a simple yet effective image deblurring method that combines salient image edges with structures. Typically, the vast majority of edge-based work focuses on advancing the salient edges information for blind image deblurring while ignoring the refined scale of the image structures. With this in mind, we show how to effectively exploit the image structure to blind image deblurring in this paper, i.e., we adopt a mutually guided image filter to guide the restoration of the image structure while salient edges provide edge information for blur kernel estimation. Thus, a more expressive deblurring model that employs L2-regularization for salient edges and image structure, together with the L0-regularization for image gradients is proposed. We find that the quality of the recovered kernel is thereby improved, and the deblurring results are more satisfactory. Experimental results show that our method outperforms state-of-the-art methods in terms of benchmark-based datasets and real scenarios, as well as computational efficiency. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.image.2022.116787 | Signal Processing: Image Communication |
Keywords | DocType | Volume |
Salient edges,Image structures,Kernel estimation,Blind image deblurring | Journal | 107 |
ISSN | Citations | PageRank |
0923-5965 | 0 | 0.34 |
References | Authors | |
0 | 5 | |