Spatial sparse scanned imaging based on compressed sensing

Qiao-Yue Zhang; Yun-Tao He; Yue-Dong Zhang

doi:10.1117/12.2245721

4 November 2016 Spatial sparse scanned imaging based on compressed sensing

Qiao-Yue Zhang, Yun-Tao He, Yue-Dong Zhang

Proceedings Volume 10026, Real-time Photonic Measurements, Data Management, and Processing II; 1002615 (2016) https://doi.org/10.1117/12.2245721
Event: SPIE/COS Photonics Asia, 2016, Beijing, China

Abstract

A new passive millimeter-wave (PMMW) image acquisition and reconstruction method is proposed based on compressed sensing (CS) and spatial sparse scanned imaging. In this method, the images are sparse sampled through a variety of spatial sparse scanned trajectories, and are reconstructed by using conjugate gradient-total variation recovery algorithm. The principles and applications of CS theories are described, and the influence of the randomness of the measurement matrix on the quality of reconstruction images is studied. Based on the above work, the qualities of the reconstructed images which were obtained by the sparse sampling method were analyzed and compared. The research results show that the proposed method can effectively reduce the image scanned acquisition time and can obtain relatively satisfied reconstructed imaging quality.

Citation Download Citation

Qiao-Yue Zhang, Yun-Tao He, and Yue-Dong Zhang "Spatial sparse scanned imaging based on compressed sensing", Proc. SPIE 10026, Real-time Photonic Measurements, Data Management, and Processing II, 1002615 (4 November 2016); https://doi.org/10.1117/12.2245721

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