An image sharpening operator combined with framelet for image deblurring
Publication in refereed journal

香港中文大學研究人員
替代計量分析
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其它資訊
摘要Image sharpening can highlight fine details in images but with a tendency of amplifying noise. This paper proposes a novel idea of incorporating an image sharpening operator into a framelet-based model for image deblurring. The proposed model is convex and hence it can be solved efficiently by the semi-proximal alternating direction method of multipliers (sPADMM) with guaranteed linear rate convergence, which covers the classical ADMM. The experimental results on different blurring kernels and Gaussian noise levels show that the proposed approach outperforms the state-of-the-art methods in terms of PSNR, SSIM, relative error, and visual quality.
著者Liu JJ, Lou YF, Ni GX, Zeng TY
期刊名稱Inverse Problems
出版年份2020
月份4
卷號36
期次4
出版社IOP PUBLISHING LTD
文章號碼045015
國際標準期刊號0266-5611
電子國際標準期刊號1361-6420
語言英式英語
關鍵詞image sharpening, wavelet frame, image restoration, alternating direction method of multipliers
Web of Science 學科類別Mathematics, Applied;Physics, Mathematical;Mathematics;Physics

上次更新時間 2020-22-09 於 01:10