In photon-limited image reconstruction, the behavior of noise at the detector end is more accurately modeled as a Poisson point process than the common choice of a Gaussian distribution. As such, to recover the original signal more accurately, a penalized negative Poisson log-likelihood function — and not a least-squares function — is minimized. In many applications, including medical imaging, additional information on the signal of interest is often available. Specifically, its maximum and minimum amplitudes might be known a priori. This paper describes an approach that incorporates this information into a sparse photon-limited recovery method by the inclusion of upper and lower bound constraints. We demonstrate the effectiveness of the proposed approach on two different low-light deblurring examples.
['Lasith Adhikari', 'Roummel F. Marcia']
Bounded sparse photon-limited image recovery