A Novel and Fast Adaptive Compressive Sampling Matching Pursuit Algorithm

Jian Zhao, Tingting Lu, Jian Jia, Chao Zhang, Weiwen Su, Rui Wang, Shunli Zhang

2016

Abstract

A weakness of compressive sampling is that it needs the information of sparsity to approximate the compressible signal. In this paper, an fast iterative reconstruction algorithm called Adaptive Compressive Sampling Matching Pursuit is presented to solve the problem mentioned above, which delivers the same guarantees as the best optimization-based approaches and get rid of the dependence on the information of sparsity. Experimental results also demonstrate that the image reconstructed performance of the proposed algorithm is improved in terms of PSNR, SNR and reconstructed time, compared to Orthogonal Matching Pursuit (OMP) and Compressive Sampling Matching Pursuit (CoSaMP).

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Paper Citation


in Harvard Style

Zhao J., Lu T., Jia J., Zhang C., Su W., Wang R. and Zhang S. (2016). A Novel and Fast Adaptive Compressive Sampling Matching Pursuit Algorithm . In ISME 2016 - Information Science and Management Engineering IV - Volume 1: ISME, ISBN 978-989-758-208-0, pages 312-317. DOI: 10.5220/0006449603120317


in Bibtex Style

@conference{isme16,
author={Jian Zhao and Tingting Lu and Jian Jia and Chao Zhang and Weiwen Su and Rui Wang and Shunli Zhang},
title={A Novel and Fast Adaptive Compressive Sampling Matching Pursuit Algorithm},
booktitle={ISME 2016 - Information Science and Management Engineering IV - Volume 1: ISME,},
year={2016},
pages={312-317},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006449603120317},
isbn={978-989-758-208-0},
}


in EndNote Style

TY - CONF
JO - ISME 2016 - Information Science and Management Engineering IV - Volume 1: ISME,
TI - A Novel and Fast Adaptive Compressive Sampling Matching Pursuit Algorithm
SN - 978-989-758-208-0
AU - Zhao J.
AU - Lu T.
AU - Jia J.
AU - Zhang C.
AU - Su W.
AU - Wang R.
AU - Zhang S.
PY - 2016
SP - 312
EP - 317
DO - 10.5220/0006449603120317