Aircraft Recognition in High-Resolution Optical Satellite Remote Sensing Images

Abstract

Automatic aircraft recognition is a challenging task. Conventional methods always extract the overall shapes of aircraft at first and then represent the aircraft based on the extracted shape with different features for recognition. The major problem of these methods is that they have a high requirement on shape extraction, which is too idealistic for targets in satellite images. In this letter, we propose a new aircraft recognition approach that can recognize aircraft robustly without perfect extraction of silhouette or shape of aircraft as a precondition, and can deal with the situation of parts missing and shadow disturbance. Specifically, a direction estimation method is proposed first to align aircraft to a same direction. Then, a reconstruction-based similarity measure is proposed, which transforms the type recognition problem into a reconstruction problem. Finally, a jigsaw matching pursuit algorithm is proposed to solve the reconstruction problem. We use panchromatic Quickbird imagery for evaluation, and the experimental results illuminate that the proposed method is effective and accurate.