Video compressive sensing using spatial domain sparsity

Jing Zheng; Eddie L. Jacobs

doi:10.1117/1.3206733

1 August 2009 Video compressive sensing using spatial domain sparsity

Jing Zheng, Eddie L. Jacobs

Author Affiliations +

Optical Engineering, Vol. 48, Issue 8, 087006 (August 2009). https://doi.org/10.1117/1.3206733

Abstract

We present a compressive sensing video acquisition scheme that relies on the sparsity properties of video in the spatial domain. In this scheme, the video sequence is represented by a reference frame, followed by the difference of measurement results between each pair of neighboring frames. The video signal is reconstructed by first reconstructing the frame differences using [script l]₁ minimization algorithm, then adding them sequentially to the reference frame. Simulation results on both simulated and real video sequences show that when the spatial changes between neighboring frames are small, this scheme provides better reconstruction results than existing compressive sensing video acquisition schemes, such as 2-D or 3-D wavelet methods and the minimum total-variance (TV) method. This scheme is suitable for compressive sensing acquisition of video sequences with relatively small spatial changes. A method that estimates the amount of spatial change based on the statistical properties of measurement results is also presented.

©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Jing Zheng and Eddie L. Jacobs "Video compressive sensing using spatial domain sparsity," Optical Engineering 48(8), 087006 (1 August 2009). https://doi.org/10.1117/1.3206733

Published: 1 August 2009

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