29 May 2013 Super-resolution mosaics from airborne video using robust gradient regularization
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Abstract
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.
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Aldo Camargo, Aldo Camargo, Qiang He, Qiang He, K. Palaniappan, K. Palaniappan, Fidel Jara, Fidel Jara, "Super-resolution mosaics from airborne video using robust gradient regularization", Proc. SPIE 8752, Modeling and Simulation for Defense Systems and Applications VIII, 875209 (29 May 2013); doi: 10.1117/12.2017930; https://doi.org/10.1117/12.2017930
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