Special Textural Aerial Image Matching Based on PCA-SIFT Feature Matching

This paper describes a novel method for special textural aerial image matching based on PCA-SIFT. Images are down sampled and subsequently, PCA-SIFT feature matching is applied. The matched points are used to calculate the homography matrix and the corresponding areas are determined between stereo image pairs. PCA-SIFT is performed again on the corresponding areas to get more matching points, and gross errors are detected. Finally, an improved least square image matching method is implemented to refine the PCA-SIFT matching results. Examples of special textural image matching demonstrate that the proposed match method can achieve subpixel accuracy and works well on images with poor texture and repetitive patterns. This method fully satisfies the requirements for automatic aerotriangulation image measurement.