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.
Highlights
The rapid development of signal processing technology has caused an increase in people’s demand for information
The aim of this study is to present a methodology for unraveling the complete firing field of a grid cell even when it is poorly represented by the recorded spikes
This study proposes a pseudo-random circulant structure on the basis of Toeplitz matrix, and introduces a method of pseudo-random circulant measurement matrix design based on chaotic sequence
Summary
The rapid development of signal processing technology has caused an increase in people’s demand for information. The large amount of information has challenged integrated information storage and effective transmission of information, and caused immense difficulties for traditional signal processing technology to meet practical demands. In 2004, Donoho et al [1,2,3,4] proposed a simultaneous sampling and compressing theory, called compressive sensing (CS). Zhang et al [16] proposed a super-resolution method for remote sensing images in the CS framework. CS theory uses a specific matrix to project the sparse or compressible signals into low-dimension space for compression. The relationship between X and Y can be expressed as Formula (1):
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