24 June 2014 Overcoming shadowing and occlusion in imagery with error-resilient processing
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Abstract
Due to the delay of sequential 3-D Lidar image acquisition while an uncooperative human target is in motion, the image may generate missing or occlusion pixels. We wish to minimize the impact of image acquisition of a moving target for aided target recognition. We apply the standard Fourier transform algorithms for an error resilience restoration to minimize the impact to the Human Visual System (HVS) which tends to overly emphasize the edge and the artificially generated discontinuity in missing pixels. We compared (i) classical phase retrieval scheme: Gerchburg-Saxon-Hayes-Papoulis (GSHP) and (ii) the Compressive Sensing scheme: Candes-Romberg-Donohoe-Tao (CRDT). The following two lessons were learned: The mechanism is based on Gibbs overshooting of a step-discontinuity. It is based on relocating the sparsely sampled zeros at missing pixel locations a la spatial and spatial frequency inner product conformal mapping property.
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Charles Hsu, Charles Hsu, Todd W. DuBosq, Todd W. DuBosq, Steven K. Moyer, Steven K. Moyer, Eric Flug, Eric Flug, Jeffrey Jenkins, Jeffrey Jenkins, Joseph S. Landa, Joseph S. Landa, Kenneth Byrd, Kenneth Byrd, Harold Szu, Harold Szu, } "Overcoming shadowing and occlusion in imagery with error-resilient processing", Proc. SPIE 9118, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XII, 91180K (24 June 2014); doi: 10.1117/12.2054409; https://doi.org/10.1117/12.2054409
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