Focus recovery for extended depth-of-field mobile imaging systems

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).