期刊
IEEE SIGNAL PROCESSING LETTERS
卷 24, 期 6, 页码 877-881出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2017.2688707
关键词
Birothogonal wavelet; heavy noise; nonlocal similarity; split Bregman; total variation (TV)
资金
- National Natural Science Foundation of China [61475016, 61301184]
- Beijing Natural Science Foundation [4154083]
- Fundamental Research Funds for the Central Universities of China [2015JBM023]
- Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry [2015-1098]
To suppress the heavy noise and keep the distinct edges of the images in the low light condition, we propose a denoising model based on the combination of total variation (TV) and nonlocal similarity in the wavelet domain. The TV regularization in the wavelet domain effectively suppresses the heavy noise with the biorthogonal wavelet function; the nonlocal similarity regularization improves the fine image details. Denoising experiments on artificially degraded and low light images show that in the heavy noise condition, the proposed denoising model can suppress the heavy noise effectively and preserve the detail of images than several state-of-the-art methods.
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