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Proceedings Paper

Bayer and panchromatic color filter array demosaicing by sparse recovery
Author(s): Mohammad Aghagolzadeh; Abdolreza Abdolhosseini Moghadam; Mrityunjay Kumar; Hayder Radha
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Paper Abstract

The utility of Compressed Sensing (CS) for demosaicing of digital images have been explored by few recent efforts. Most recently, a Compressive Demosaicing [3] framework, based on employing a random panchromatic Color Filter Array (CFA) at the sensing stage, has provided compelling CS-based demosaicing results by visually outperforming other leading techniques. Meanwhile, it is well known that the Bayer pattern is arguably the most popular CFA used in low-cost consumer digital cameras. In this paper, we explore and compare the Bayer and random panchromatic CFA structures using a generic approach for demosaicing of images based on recent advances in the field of CS. In particular, a key objective of this work is to provide a comparative analysis between these two CFA patterns (Bayer and random panchromatic) under the general umbrella of sparse recovery, which represents the cornerstone of CS-based decoding. We demonstrate the viability of the Bayer pattern under certain CS conditions. Meanwhile, we show that a random panchromatic CFA, which meets certain incoherence constraints, can visually outperform a Bayer based sparse recovery. As illustrated in our simulation results, a panchromatic CFA is more consistent in terms of providing better visual quality when tested on a wide range of color images.

Paper Details

Date Published: 24 January 2011
PDF: 11 pages
Proc. SPIE 7876, Digital Photography VII, 787603 (24 January 2011); doi: 10.1117/12.872533
Show Author Affiliations
Mohammad Aghagolzadeh, Michigan State Univ. (United States)
Abdolreza Abdolhosseini Moghadam, Michigan State Univ. (United States)
Mrityunjay Kumar, Eastman Kodak Co. (United States)
Hayder Radha, Michigan State Univ. (United States)

Published in SPIE Proceedings Vol. 7876:
Digital Photography VII
Francisco H. Imai; Feng Xiao, Editor(s)

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