A new image denoising method based on shearlet shrinkage and improved total variation

Authors:
Ying Li;Rui-ming Chen;Shi Liang
Affiliations:
School of Computer Science, Northwestern Polytechnical University, Xi'an, Shannxi, China;School of Computer Science, Northwestern Polytechnical University, Xi'an, Shannxi, China;School of Computer Science, Northwestern Polytechnical University, Xi'an, Shannxi, China
Venue:
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Year:
2011

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Abstract

This paper presents a new image denoising scheme by combining the shearlet shrinkage and improved total variation (TV). According to the artifacts that appear in the result image after applying shearlet denoising approach, the image is further denoised by a TV model, which is improved on the fidelity term. Experiments show that the proposed scheme can remove image noise and preserve the edge texture. Meanwhile, it can remove Gibbs-like artifacts effectively and has lower computational complexity.