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2 June 2012Reconstruction algorithm of infrared video image based on compressed sensing
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
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Qing Xu, Lijun Yun, Junsheng Shi, "Reconstruction algorithm of infrared video image based on compressed sensing," Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833418 (2 June 2012);