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Proceedings Paper

Reconstruction algorithm of infrared video image based on compressed sensing
Author(s): Qing Xu; Lijun Yun; Junsheng Shi
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Paper Abstract

Compressed sensing is a novel signal sampling theory emerging recently. It is a theory that signals could be sampled far below the Nyquist sampling rate. This paper introduces compressed sensing theory into the application of infrared video, proposes a new residual reconstruction algorithm, and establishes a new infrared video codec model with random Gaussian matrix as the measurement matrix and with orthogonal matching pursuit algorithm as the reconstruction method. On the platform of Matlab, this paper performs the reconstruction of infrared video frames. The simulation results verify that the proposed algorithm can provide a good visual quality and speed up evidently by comparison with conventional algorithm.

Paper Details

Date Published: 2 June 2012
PDF: 7 pages
Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833418 (2 June 2012); doi: 10.1117/12.946580
Show Author Affiliations
Qing Xu, Yunnan Normal Univ. (China)
Lijun Yun, Yunnan Normal Univ. (China)
Junsheng Shi, Yunnan Normal Univ. (China)

Published in SPIE Proceedings Vol. 8334:
Fourth International Conference on Digital Image Processing (ICDIP 2012)
Mohamed Othman; Sukumar Senthilkumar; Xie Yi, Editor(s)

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