Seminar

Speaker : Jae Kyu Choi (Professor, School of Mathematical Sciences, Tongji University, Shanghai, China)

Abstract)

Recently, mapping a signal/image into a low rank Hankel/Toeplitz matrix has become an emerging alternative to the traditional sparse regularization, due to its ability to alleviate the basis mismatch between the true support in the continuous domain and the discrete grid. In this talk, we introduce a novel interpretation on the structured low rank matrix framework for image restoration. We observe that the SVD of a low rank Hankel matrix corresponds to a tight wavelet frame system which can represent the image with sparse coefficients. Based on this observation, we introduce two image restoration models; a balanced approach based on the data driven tight frame, and a two-stage approach based on the analysis approach.