<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In order to improve the quality of the reconstruction image which using Compressive sensing(CS) algorithm. Based on improved measurement matrix combined with CS Matching Pursuit(CoSaMP)algorithm, this paper presents a kind of Fourier Ring Compressive Sampling Matching Pursuit (FR-CoSaMP) algorithm. The algorithm superimposed deterministic ring measurement matrix to optimize measurement process on the basis of Fourier measurement matrix. And solve the iterative inverse operation by using FFT fast Fourier calculation method, which can make the measurement information more complete, and speed up the signal reconstruction. Then introduces the mathematical framework and algorithmic processes of the FR-CoSaMP algorithm in details. Finally, compare these types of traditional algorithms and the improved algorithm by analysis and simulation. The results show that, under the same image sparsity and measurement scale, the improved FR-CoSaMP algorithm has better performance in terms of the image reconstruction.</p></abstract>

In order to improve the quality of the reconstruction image which using Compressive sensing(CS) algorithm. Based on improved measurement matrix combined with CS Matching Pursuit(CoSaMP)algorithm, this paper presents a kind of Fourier Ring Compressive Sampling Matching Pursuit (FR-CoSaMP) algorithm. The algorithm superimposed deterministic ring measurement matrix to optimize measurement process on the basis of Fourier measurement matrix. And solve the iterative inverse operation by using FFT fast Fourier calculation method, which can make the measurement information more complete, and speed up the signal reconstruction. Then introduces the mathematical framework and algorithmic processes of the FR-CoSaMP algorithm in details. Finally, compare these types of traditional algorithms and the improved algorithm by analysis and simulation. The results show that, under the same image sparsity and measurement scale, the improved FR-CoSaMP algorithm has better performance in terms of the image reconstruction.

Improved Measure Algorithm Based On Cosamp For Image Recovery

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Improved Measure Algorithm Based On Cosamp For Image Recovery"}

In order to improve the quality of the reconstruction image which using Compressive sensing(CS) algorithm. Based on improved measurement matrix combined with...

Improved Measure Algorithm Based On Cosamp For Image Recovery

Publicado en línea: 27 dic 2017

Páginas: 724 - 739

Recibido: 06 feb 2014

Aceptado: 01 jun 2014

DOI: https://doi.org/10.21307/ijssis-2017-678

Palabras clave
Compressed sensing, Measurement Matrix, Fourier Ring, Orthogonal Matching

© 2014 Guohui Wu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Improved Measure Algorithm Based On Cosamp For Image Recovery

Publicado en línea: 27 dic 2017

Páginas: 724 - 739

Recibido: 06 feb 2014

Aceptado: 01 jun 2014

DOI: https://doi.org/10.21307/ijssis-2017-678

Palabras claveCompressed sensing, Measurement Matrix, Fourier Ring, Orthogonal Matching

© 2014 Guohui Wu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Palabras clave
Compressed sensing, Measurement Matrix, Fourier Ring, Orthogonal Matching