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.

中文翻译：

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改进SAR图像匹配的最优纹理图像重建方法

图像匹配是大多数合成孔径雷达（SAR）图像应用中迈出的重要一步。在这项研究中，提出了一种用于纹理图像重建的方法，以改善SAR图像匹配。此方法包括三个主要步骤。首先，提取纹理特征。使用提取的特征创建第二个最佳纹理图像（OTI）。使用猫群优化算法进行纹理优化。代价函数是从加速的鲁棒特征（SURF）图像匹配算法获得的正确匹配点的数量。最终，对立体声OTI对上的对应点进行匹配。在由RADARSAT-2，ALOS-PALSAR和Sentinel-1组成的星载SAR图像对上进行了实验。