Super-resolution Mosaics from Airborne Video Using Robust Gradient Regularization

摘要

Unmanned Aircraft Systems (UAS) have been used in many military and civil applications, particularly surveillance. One of the best ways to use the capacity of a UAS imaging system is by constructing a mosaic or panorama of the recorded video. This paper presents a novel algorithm for the construction of super-resolution mosaicking. The algorithm is based on the Conjugate Gradient (CG) method. Geman -McClure prior is used together with four different cliques to deal with the ill-conditioned inverse problem and to preserve edges. We present the results with synthetic and real UAS surveillance data, resulting in a great improvement of the visual resolution. For the case of synthetic images, we obtained a PSNR of 47.0 dB, as well as a significant increase in the details visible for the case of real UAS frames in only ten iterations.