Compressive Sensing by Colpitts Chaotic Oscillator for Image Sensors

Li Liu; Peng Yang; Jianguo Zhang; Guifen Wei

doi:10.21307/ijssis-2017-804

Abstract

Compressive sensing uses simultaneous sensing and compression to provide an efficient image acquisition technique and it has been demonstrated in optical and electrical image sensors. To guarantee exact recovery from sparse measurements, specific sensing matrix, which satisfies the Restricted Isometry Property (RIP), should be well chosen. Toeplitz-structured chaotic sensing matrix constructed by Logistic map has been proved to satisfy RIP with high probability. In this paper, we propose that chaotic sequence sampled from Colpitts oscillator can also be used to generate Toeplitz- structured chaotic sensing matrix. Simulation results show that the proposed Colpitts chaotic sensing matrix has similar performance to random matrix or other chaotic matrix for exact reconstructing compressible signals and images from fewer measurements.

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Compressive Sensing by Colpitts Chaotic Oscillator for Image Sensors

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