Super-resolution reconstruction for image breaks through the resolution limit of imaging systems without hardware change. The algorithm of projection onto convex set (POCS) is a typical super-resolution reconstruction algorithm in spatial domain. The classical algorithm of POCS lacks the overall constraint for the image, and the convergence rate for iteration is incontrollable. A new super-resolution restoration algorithm for image based on entropy constraint and POCS is proposed in this paper, and experiments with optical and millimeter wave images demonstrate that the new algorithm is effective in improving the precision of super-resolution restoration.
Optics Temperature-Dependent Nonuniformity Correction Via $\ell _{0}$ -Regularized Prior for Airborne Infrared Imaging Systems
