Open AccessApplication of two-dimensional truncated singular value decomposition in image restoration
Author(s) -
Hongyu Zhou,
Kou Ting,
Shanjia Xu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1976/1/012009
Subject(s) - singular value decomposition , image restoration , regularization (linguistics) , image (mathematics) , singular value , mathematics , algorithm , decomposition , mathematical optimization , computer science , scale (ratio) , artificial intelligence , image processing , physics , chemistry , organic chemistry , eigenvalues and eigenvectors , quantum mechanics
Large solution size and ill-posed problem often exists in image restoration. In order to overcome these problems, the application of two-dimensional truncated singular value decomposition(2-D TSVD) in large-scale image restoration is studied in this paper. The 2-D TSVD overcomes the inherent ill-posed problem and also solves the problem caused by limited storage in image restoration, which plays a regularization role. Experimental results show that this method is very effective in image restoration.