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Appl. Sci. 2018, 8(8), 1293; https://doi.org/10.3390/app8081293

Single-Pixel Color Imaging Method with a Compressive Sensing Measurement Matrix

1
College of Information Science and Engineering, Northeastern University, No.3-11, WenHua Road, Heping District, Shenyang 110819, China
2
Shenyang Institute of Automation Chinese Academy of Science, No.114, NanTa Street, ShenHe District, Shenyang 110016, China
*
Author to whom correspondence should be addressed.
Received: 18 June 2018 / Revised: 28 July 2018 / Accepted: 30 July 2018 / Published: 3 August 2018
(This article belongs to the Section Optics and Lasers)
View Full-Text   |   Download PDF [1839 KB, uploaded 3 August 2018]   |  

Abstract

Compressive sensing theory has addressed the limitations of traditional methods in the field of information technology, and led to a revolution. On the basis of compressive sensing theory research, this study utilized the exterior determinacy and inherent randomness of chaotic sequences, designed a pseudo-random circulant measurement matrix based on chaotic sequence. Compared with other deterministic measurement matrices, the restoration effect of the designed measurement matrix remarkably improved and showed advantages in hardware and storage. Then, this study developed a single-pixel imaging scheme that could accurately obtain color information. The proposed improved measurement matrix combined with the hardware system could accurately reconstruct color images and had good robustness according to various experimental data. View Full-Text
Keywords: single imaging system; compressive sensing; measurement matrix single imaging system; compressive sensing; measurement matrix
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Jia, T.; Chen, D.; Wang, J.; Xu, D. Single-Pixel Color Imaging Method with a Compressive Sensing Measurement Matrix. Appl. Sci. 2018, 8, 1293.

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