Three deterministic constructions of compressed sensing matrices with low coherence
Sign Up to like & getrecommendations! Published in 2019 at "Cryptography and Communications"
DOI: 10.1007/s12095-019-00375-5
Abstract: Matrices with low coherence have applications in compressed sensing and some other areas. In this paper, we present three deterministic constructions of compressed sensing matrices by using algebraic and combinatorial methods. We show that our… read more here.
Keywords: deterministic constructions; compressed sensing; three deterministic; matrices low ... See more keywords
Multi-Matrices Low-Rank Decomposition With Structural Smoothness for Image Denoising
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2019.2890880
Abstract: In this paper, we propose a multi-matrices low-rank decomposition method for image denoising. In this new method, the total variation (TV) norm is incorporated into low-rank approximation analysis to achieve structural smoothness and to improve… read more here.
Keywords: rank decomposition; low rank; rank; structural smoothness ... See more keywords