Image Deblurring using Adaptive Alternate Direction Multiplier Overlapping Group Sparsity Method
[1]Wang Jie,Li Shengguang,Song Yifan,et al.Image Deblurring using Adaptive Alternate Direction Multiplier Overlapping Group Sparsity Method[J].Journal of Zhengzhou University (Engineering Science),2018,39(05):52-57.[doi:10.13705/j.issn.1671-6833.2018.05.017]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
39卷
Number of periods:
2018 05
Page number:
52-57
Column:
Public date:
2018-08-21
- Title:
- Image Deblurring using Adaptive Alternate Direction Multiplier Overlapping Group Sparsity Method
- Keywords:
- Deblurring; Total Variation; Overlapping; Group Sparse; ADMM; Adaptive
- CLC:
- -
- DOI:
- 10.13705/j.issn.1671-6833.2018.05.017
- Abstract:
- Image debluring technology played an important part in the image processing field. Total variables regularization with overlapping sparisity was gradually applied to the image deblurring problem. It could preserve image edge characteristics and suppress the generation of the staicase effect. When using the alternate direcction multiplier(ADMM) method to solve the overlapping group sparsity total variables model, the penalty factor could greatly influence the deblurring process and it was not easy to adjust. Therefore, a method was proposed to adaptively adjust the penalty factor according to the recovered image when the model was being optimized. This method adaptively restored the best picture and ensured the robustness of the algorithm while guaranteening the speed of calculation. Experimental results showed that the proposed method outperformed other recovery models in terms of PSNR, SNR, relative error and other evaluation indices.
- References:
- -
- Similar References:
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Last Update:
2018-08-22