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      Spatial Domain Terahertz Image Reconstruction Based on Dual Sparsity Constraints

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          Abstract

          Terahertz time domain spectroscopy imaging systems suffer from the problems of long image acquisition time and massive data processing. Reducing the sampling rate will lead to the degradation of the imaging reconstruction quality. To solve this issue, a novel terahertz imaging model, named the dual sparsity constraints terahertz image reconstruction model (DSC-THz), is proposed in this paper. DSC-THz fuses the sparsity constraints of the terahertz image in wavelet and gradient domains into the terahertz image reconstruction model. Differing from the conventional wavelet transform, we introduce a non-linear exponentiation transform into the shift invariant wavelet coefficients, which can amplify the significant coefficients and suppress the small ones. Simultaneously, the sparsity of the terahertz image in gradient domain is used to enhance the sparsity of the image, which has the advantage of edge preserving property. The split Bregman iteration scheme is utilized to tackle the optimization problem. By using the idea of separation of variables, the optimization problem is decomposed into subproblems to solve. Compared with the conventional single sparsity constraint terahertz image reconstruction model, the experiments verified that the proposed approach can achieve higher terahertz image reconstruction quality at low sampling rates.

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          Enhancing Sparsity by Reweighted ℓ 1 Minimization

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            Bregman Iterative Algorithms for $\ell_1$-Minimization with Applications to Compressed Sensing

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              • Record: found
              • Abstract: not found
              • Article: not found

              Fixed-Point Continuation for $\ell_1$-Minimization: Methodology and Convergence

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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                15 June 2021
                June 2021
                : 21
                : 12
                : 4116
                Affiliations
                [1 ]School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou 450001, China; yyjing21@ 123456126.com
                [2 ]Key Laboratory of Grain Information Processing & Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China
                Author notes
                [* ]Correspondence: rxz235@ 123456haut.edu.cn
                Article
                sensors-21-04116
                10.3390/s21124116
                8232612
                385b8700-2f36-461c-9ecc-338b18554e00
                © 2021 by the authors.

                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/).

                History
                : 07 May 2021
                : 10 June 2021
                Categories
                Article

                Biomedical engineering
                terahertz,imaging model,exponentiation shift invariant wavelet,gradient domain,split bregman iteration

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