LI Min, XU Chen. Variational Image Restoration and Decomposition in Shearlet Smoothness Spaces[J]. Chinese Journal of Electronics, 2017, 26(5): 1017-1021. doi: 10.1049/cje.2017.08.021
Citation: LI Min, XU Chen. Variational Image Restoration and Decomposition in Shearlet Smoothness Spaces[J]. Chinese Journal of Electronics, 2017, 26(5): 1017-1021. doi: 10.1049/cje.2017.08.021

Variational Image Restoration and Decomposition in Shearlet Smoothness Spaces

doi: 10.1049/cje.2017.08.021
Funds:  This work is supported by the National Natural Science Foundation of China (No.61472257, No.61402290) and Shenzhen Basis Research Project (No.JCYJ20160520161847267).
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  • Corresponding author: XU Chen (corresponding author) was born in Zhejiang Province. He received the B.S. and M.S. degrees in mathematics from Xidian University in 1986 and 1989, the Ph.D. degree in mathematics from Xi'an Jiaotong University in 1992 respectively. He is now a professor at Shenzhen University. His research interests include information and computational science, analysis and application of wavelet. (Email:xuchen szu@szu.edu.cn)
  • Received Date: 2015-09-17
  • Rev Recd Date: 2016-08-11
  • Publish Date: 2017-09-10
  • We present the shearlet-based variational model for image restoration and decomposition. The new model can be seen as generalizations of DaubechiesTeschke's model. By using regularization term in shearlets smoothness spaces, and writing the problem in a shearlet framework, we obtain elegant shearlet shrinkage schemes. Furthermore, the model allows us to incorporate general bounded linear blur operators into the problem. The experiments on denoising, deblurring and decomposition of images show that our algorithm is very efficient.
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