A Novel Iterative Thresholding Algorithm Based on Plug-and-Play Priors for Compressive Sampling

We propose a novel fast iterative thresholding algorithm for image compressive sampling (CS) recovery using three existing denoisers—i.e., TV (total variation), wavelet, and BM3D (block-matching and 3D filtering) denoisers. Through the use of the recently introduced plug-and-play prior approach, we...

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Main Authors: Lingjun Liu, Zhonghua Xie, Cui Yang
Format: Article
Language:English
Published: MDPI AG 2017-06-01
Series:Future Internet
Subjects:
Online Access:http://www.mdpi.com/1999-5903/9/3/24
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author Lingjun Liu
Zhonghua Xie
Cui Yang
author_facet Lingjun Liu
Zhonghua Xie
Cui Yang
author_sort Lingjun Liu
collection DOAJ
description We propose a novel fast iterative thresholding algorithm for image compressive sampling (CS) recovery using three existing denoisers—i.e., TV (total variation), wavelet, and BM3D (block-matching and 3D filtering) denoisers. Through the use of the recently introduced plug-and-play prior approach, we turn these denoisers into CS solvers. Thus, our method can jointly utilize the global and nonlocal sparsity of images. The former is captured by TV and wavelet denoisers for maintaining the entire consistency; while the latter is characterized by the BM3D denoiser to preserve details by exploiting image self-similarity. This composite constraint problem is then solved with the fast composite splitting technique. Experimental results show that our algorithm outperforms several excellent CS techniques.
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spelling doaj.art-b8dca0a9a3c44d73838a80dee5d062e42022-12-22T01:38:42ZengMDPI AGFuture Internet1999-59032017-06-01932410.3390/fi9030024fi9030024A Novel Iterative Thresholding Algorithm Based on Plug-and-Play Priors for Compressive SamplingLingjun Liu0Zhonghua Xie1Cui Yang2School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, ChinaSchool of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, ChinaSchool of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, ChinaWe propose a novel fast iterative thresholding algorithm for image compressive sampling (CS) recovery using three existing denoisers—i.e., TV (total variation), wavelet, and BM3D (block-matching and 3D filtering) denoisers. Through the use of the recently introduced plug-and-play prior approach, we turn these denoisers into CS solvers. Thus, our method can jointly utilize the global and nonlocal sparsity of images. The former is captured by TV and wavelet denoisers for maintaining the entire consistency; while the latter is characterized by the BM3D denoiser to preserve details by exploiting image self-similarity. This composite constraint problem is then solved with the fast composite splitting technique. Experimental results show that our algorithm outperforms several excellent CS techniques.http://www.mdpi.com/1999-5903/9/3/24compressive samplingplug-and-play priorBM3Dcomposite splitting
spellingShingle Lingjun Liu
Zhonghua Xie
Cui Yang
A Novel Iterative Thresholding Algorithm Based on Plug-and-Play Priors for Compressive Sampling
Future Internet
compressive sampling
plug-and-play prior
BM3D
composite splitting
title A Novel Iterative Thresholding Algorithm Based on Plug-and-Play Priors for Compressive Sampling
title_full A Novel Iterative Thresholding Algorithm Based on Plug-and-Play Priors for Compressive Sampling
title_fullStr A Novel Iterative Thresholding Algorithm Based on Plug-and-Play Priors for Compressive Sampling
title_full_unstemmed A Novel Iterative Thresholding Algorithm Based on Plug-and-Play Priors for Compressive Sampling
title_short A Novel Iterative Thresholding Algorithm Based on Plug-and-Play Priors for Compressive Sampling
title_sort novel iterative thresholding algorithm based on plug and play priors for compressive sampling
topic compressive sampling
plug-and-play prior
BM3D
composite splitting
url http://www.mdpi.com/1999-5903/9/3/24
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