Robust Extraction and Super-Resolution of Low-Resolution Flying Airplane From Satellite Video

Abstract

Extracting the flying airplane from the satellite video and enhancing its resolution are significant and demanding tasks in the remote sensing community. The challenge mainly lies in that the flying airplane target in the satellite video often suffers from detail loss due to complex background and limited spaceborne imaging device. In this article, a novel constructive model is proposed to model the airplane of low resolution for more complete extraction, and a new reflective symmetry shape prior is integrated into the super-resolution process to obtain the higher resolution result. Concretely, each frame can be decomposed as a linear combination of foreground and background with specific mixture ratios. With the assumption of uniform linear motion and the rigidity of the airplane, a periodic change of mixture ratios through frames is induced, which can construct the airplane as complete as possible by adopting the proposed iterative matting optimization. To further enhance the resolution of the extracted airplane, an improved alternating direction method of multipliers (ADMM) is utilized to solve the super-resolution problem with the reflective symmetry of the shape as prior. The effectiveness of our method with respect to extraction and super-resolution is borne out by the experiments on both synthetic and real data.