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Proceedings Paper

Spatial sparse scanned imaging based on compressed sensing
Author(s): Qiao-Yue Zhang; Yun-Tao He; Yue-Dong Zhang
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Paper 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.

Paper Details

Date Published: 4 November 2016
PDF: 9 pages
Proc. SPIE 10026, Real-time Photonic Measurements, Data Management, and Processing II, 1002615 (4 November 2016); doi: 10.1117/12.2245721
Show Author Affiliations
Qiao-Yue Zhang, BeiHang Univ. (China)
Yun-Tao He, BeiHang Univ. (China)
Yue-Dong Zhang, Beijing Institute Of Space Mechanics and Electricity (China)

Published in SPIE Proceedings Vol. 10026:
Real-time Photonic Measurements, Data Management, and Processing II
Ming Li; Bahram Jalali; Keisuke Goda; Kevin K. Tsia, Editor(s)

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