Abstract

ABSTRACT Feature matching in optical remote sensing images usually suffers from significant intensity differences and background variations. In this paper, an effective image matching approach is proposed to match salient structures in optical remote sensing images. The proposed method consists of three main steps. In the first step, EDLines algorithm is implemented to extract straight lines from two corresponding images, and these lines are further processed and divided into line segments for feature matching. In the second step, a robust descriptor namely line segment context (LSC) descriptor is computed for each line segment. An iterative procedure that combines line segment description and feature matching is presented for accurate matching. Finally, the consistency check is implemented to further refine the matching results. We conduct the experiments on pairs of optical remote sensing images, and experimental results show that the proposed method can automatically and robustly generate line segment features and achieve favourable performance compared to existing image matching approaches.

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