The measurement matrix optimized by information operator improvement

The signal sample tool which is called measurement matrix or observation matrix is very important for the theory of compressive sensing. Decreasing the correlation between any two different columns of the information operator is the basis of the design and optimization of the measurement matrix. Bas...

Full description

Saved in:
Bibliographic Details
Main Authors: Pan, Jinfeng, Yin, Liju, Shen, Jin, Liu, Faying, Gao, Mingliang, Ma, Lixiu, Zou, Guofeng
Format: Conference Proceeding
Language:English
Subjects:
Coherence
Compressed sensing
compressive sensing
Correlation
Image reconstruction
information operator
Matching pursuit algorithms
Matrix decomposition
measurement matrix
QR decomposition
Sparse matrices
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The signal sample tool which is called measurement matrix or observation matrix is very important for the theory of compressive sensing. Decreasing the correlation between any two different columns of the information operator is the basis of the design and optimization of the measurement matrix. Based on it, the non-diagonal elements of the upper triangular matrix of the QR decomposition of information operator was set to zero to increase its minimum singular value and decrease the column correlation of information operator, and thus this method can enhance the performance of the measurement matrix. Experiments illustrate that when the algorithm of this paper is utilized, the recovery error of signals and images are both diminished.
ISSN:2688-0938
DOI:10.1109/CAC48633.2019.8996805