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An Adaptive Rate Blocked Compressive Sensing Method for Video
An adaptive rate Compressive Sensing (CS) method for video signals is proposed. The Blocked Compressive Sensing (BCS) scheme is adopted in this method. Firstly, each video frame is blocked and measured by the BCS scheme, and then the mean and variance of each image block are estimated by observing t...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8394679/ https://www.ncbi.nlm.nih.gov/pubmed/34441142 http://dx.doi.org/10.3390/e23081002 |
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author | Wang, Jianming Chen, Jianhua |
author_facet | Wang, Jianming Chen, Jianhua |
author_sort | Wang, Jianming |
collection | PubMed |
description | An adaptive rate Compressive Sensing (CS) method for video signals is proposed. The Blocked Compressive Sensing (BCS) scheme is adopted in this method. Firstly, each video frame is blocked and measured by the BCS scheme, and then the mean and variance of each image block are estimated by observing the CS measurement results. Using the mean and variance of each image block, the sparsity of the block is estimated and then the block can be classified. Adaptive rate sampling is realized by assigning different sampling rates to different classes. At the same time, in order to make better use of the correlation between video frames, a reference block subtraction method is also designed in this paper, which uses the estimates of the sparsity of image blocks as the basis for the reference block update. All operations of the proposed method only depend on the CS measurement results of image blocks and all calculations are simple. Thus, the proposed method is suitable for implementation in CS sampling devices with limited computational performance. Experiment results show that, compared with the actual values, the sparsity estimates and block classification results of the proposed method are accurate. Compared with the latest adaptive Compressive Video Sensing methods, the reconstructed image quality of the proposed method is better. |
format | Online Article Text |
id | pubmed-8394679 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83946792021-08-28 An Adaptive Rate Blocked Compressive Sensing Method for Video Wang, Jianming Chen, Jianhua Entropy (Basel) Article An adaptive rate Compressive Sensing (CS) method for video signals is proposed. The Blocked Compressive Sensing (BCS) scheme is adopted in this method. Firstly, each video frame is blocked and measured by the BCS scheme, and then the mean and variance of each image block are estimated by observing the CS measurement results. Using the mean and variance of each image block, the sparsity of the block is estimated and then the block can be classified. Adaptive rate sampling is realized by assigning different sampling rates to different classes. At the same time, in order to make better use of the correlation between video frames, a reference block subtraction method is also designed in this paper, which uses the estimates of the sparsity of image blocks as the basis for the reference block update. All operations of the proposed method only depend on the CS measurement results of image blocks and all calculations are simple. Thus, the proposed method is suitable for implementation in CS sampling devices with limited computational performance. Experiment results show that, compared with the actual values, the sparsity estimates and block classification results of the proposed method are accurate. Compared with the latest adaptive Compressive Video Sensing methods, the reconstructed image quality of the proposed method is better. MDPI 2021-07-31 /pmc/articles/PMC8394679/ /pubmed/34441142 http://dx.doi.org/10.3390/e23081002 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Jianming Chen, Jianhua An Adaptive Rate Blocked Compressive Sensing Method for Video |
title | An Adaptive Rate Blocked Compressive Sensing Method for Video |
title_full | An Adaptive Rate Blocked Compressive Sensing Method for Video |
title_fullStr | An Adaptive Rate Blocked Compressive Sensing Method for Video |
title_full_unstemmed | An Adaptive Rate Blocked Compressive Sensing Method for Video |
title_short | An Adaptive Rate Blocked Compressive Sensing Method for Video |
title_sort | adaptive rate blocked compressive sensing method for video |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8394679/ https://www.ncbi.nlm.nih.gov/pubmed/34441142 http://dx.doi.org/10.3390/e23081002 |
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