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Proceedings Paper

Focus recovery for extended depth-of-field mobile imaging systems
Author(s): Dan Lelescu; Kartik Venkataraman; Rob Mullis; Pravin Rao; Cheng Lu; Junqing Chen; Brian Keelan
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Paper Abstract

We describe a solution for image restoration in a computational camera known as an extended depth of field (EDOF) system. The specially-designed optics produce point spread functions that are roughly invariant with object distance in a range. However, this invariance involves a trade-off with the peak sharpness of the lens. The lens blur is a function of lens field-height, and the imaging sensor introduces signal-dependent noise. In this context, the principal contributions of this paper are: a) the modeling of the EDOF focus recovery problem; and b) the adaptive EDOF focus recovery approach, operating in signal-dependent noise. The focus recovery solution is adaptive to complexities of an EDOF imaging system, and performs a joint deblurring and noise suppression. It also adapts to imaging conditions by accounting for the state of the sensor (e.g., low-light conditions).

Paper Details

Date Published: 2 September 2009
PDF: 12 pages
Proc. SPIE 7443, Applications of Digital Image Processing XXXII, 74430H (2 September 2009); doi: 10.1117/12.824623
Show Author Affiliations
Dan Lelescu, Aptina Imaging (United States)
Kartik Venkataraman, Pelican Imaging (United States)
Rob Mullis, Pelican Imaging (United States)
Pravin Rao, Pixim, Inc. (United States)
Cheng Lu, Aptina Imaging (United States)
Junqing Chen, Aptina Imaging (United States)
Brian Keelan, Aptina Imaging (United States)


Published in SPIE Proceedings Vol. 7443:
Applications of Digital Image Processing XXXII
Andrew G. Tescher, Editor(s)

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