Motion-less super-resolution under blind condition using sparse optimization
Yoshitaka Izumi, Sota Kawakami, Hiroyuki Kudo · 2020
The purpose of this paper is two-fold. First, we develop a regularized and accelerated version of Ahmed's multi-channel blind deconvolution algorithm based on low-rank matrix recovery. Second, we apply the developed algorithm to motion-less super-resolution problem, which aims at recovering a high-resolution image from a set of differently blurred low-resolution images. We demonstrate performances of the proposed method by simulation studies and real-image experiments.