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Proceedings Paper

Compressive light field imaging with weighted random projections
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Paper Abstract

Traditional light field imagers do not exploit the inherent spatio-angular correlations in light field of natural scenes towards reducing the number of measurements and minimizing the spatio-angular resolution trade-off. Here we describe a compressive light field imager that utilizes the prior knowledge of sparsity/compressibility along the spatial dimension of the light field to make compressive measurements. The reconstruction performance is analyzed for three choices of measurement bases: wavelet, random, and weighted random using a simulation study. We find that the weighted random bases outperforms both the coherent wavelet basis and the incoherent random basis on a light field data set. Specifically, the simulation study shows that the weighted random basis achieves 44% to 50% lower reconstruction error compared to wavelet and random bases for a compression ratio of three.

Paper Details

Date Published: 8 September 2011
PDF: 8 pages
Proc. SPIE 8165, Unconventional Imaging, Wavefront Sensing, and Adaptive Coded Aperture Imaging and Non-Imaging Sensor Systems, 816519 (8 September 2011); doi: 10.1117/12.894367
Show Author Affiliations
Amit Ashok, College of Optical Sciences, The Univ. of Arizona (United States)
Mark A. Neifeld, College of Optical Sciences, The Univ. of Arizona (United States)
The Univ. of Arizona (United States)


Published in SPIE Proceedings Vol. 8165:
Unconventional Imaging, Wavefront Sensing, and Adaptive Coded Aperture Imaging and Non-Imaging Sensor Systems
Stanley Rogers; Jean J. Dolne; David P. Casasent; Thomas J. Karr; Victor L. Gamiz, Editor(s)

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