Abstract
Image matching is an important step that is taken in most synthetic aperture radar (SAR) images applications. In this study, a method is proposed for texture image reconstruction to improve SAR image matching. This method consists of three major steps. First, textural features are extracted. Second optimal texture images (OTIs) are created using extracted features. Texture optimisation is conducted using a cat swarm optimisation algorithm. The cost function is the number of correct matched points that are obtained from speeded-up robust features (SURFs) image matching algorithm. Finally, corresponding points on stereo OTI pairs are matched. Experiments were conducted on spaceborne SAR image pairs consist of RADARSAT-2, ALOS-PALSAR, and Sentinel-1. Results demonstrate that the proposed method has better results in terms of the number of matched points compared to the result of the original SURF and scale-invariant feature transform methods as two common matching methods.
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