Paper
24 June 2014 Overcoming shadowing and occlusion in imagery with error-resilient processing
Charles Hsu, Todd W. DuBosq, Steven K. Moyer, Eric Flug, Jeffrey Jenkins, Joseph S. Landa, Kenneth Byrd, Harold Szu
Author Affiliations +
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.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Charles Hsu, Todd W. DuBosq, Steven K. Moyer, Eric Flug, Jeffrey Jenkins, Joseph S. Landa, Kenneth Byrd, and 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); https://doi.org/10.1117/12.2054409
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KEYWORDS
Fourier transforms

Phase retrieval

Iris

3D acquisition

3D image processing

Image acquisition

Image processing

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