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2 September 2009 Focus recovery for extended depth-of-field mobile imaging systems
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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).
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dan Lelescu, Kartik Venkataraman, Rob Mullis, Pravin Rao, Cheng Lu, Junqing Chen, and Brian Keelan "Focus recovery for extended depth-of-field mobile imaging systems", Proc. SPIE 7443, Applications of Digital Image Processing XXXII, 74430H (2 September 2009); https://doi.org/10.1117/12.824623
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