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Conventional integer order differential operators suffer from poor feature detection accuracy and noise immunity, which leads to image misalignment. A new affine-based fractional order feature detection algorithm is proposed to detect syntactic and semantic structures from the backscattered signal of a TerraSAR-X band stripmap image. To further improve the alignment accuracy, we propose to adapt a view synthesis approach in the standard pipeline of feature-based image alignment. Experiments were performed to test the effectiveness and robustness of the view synthesis approach using a fractional order feature detector. The evaluation results showed that the proposed method achieves high precision and robust alignment of look-angle-varied TerraSAR-X images. The affine features detected using the fractional order operator are more stable and have strong capacity to reduce sturdy speckle noise.

A Framework for Image Alignment of TerraSAR-X Images Using Fractional Derivatives and View Synthesis Approach