@inproceedings{ed4a2f697e1942a69f72ce9abfacb7fc,
title = "Spatial sparse scanned imaging based on compressed sensing",
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.",
keywords = "compressed sensing, conjugate gradient-total variation algorithm, PMMW imaging, sparse scanned trajectories",
author = "Zhang, \{Qiao Yue\} and He, \{Yun Tao\} and Zhang, \{Yue Dong\}",
note = "Publisher Copyright: {\textcopyright} 2016 SPIE.; Real-Time Photonic Measurements, Data Management, and Processing II ; Conference date: 12-10-2016 Through 13-10-2016",
year = "2016",
doi = "10.1117/12.2245721",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Bahram Jalali and Keisuke Goda and Tsia, \{Kevin K.\} and Ming Li",
booktitle = "Real-Time Photonic Measurements, Data Management, and Processing II",
address = "美国",
}