Stitching algorithm for sea and air image under large parallax
In view of the problems of sparse feature points and distorted ghosting after registration in the task of stitch-ing unevenly weak texture backgrounds represented by sea-sky background images with large parallax,a multi-level com-posite feature extraction and optimal seam search algorithm combined with information entropy is proposed.Firstly,the im-ages to be stitched are preprocessed by side window filtering to construct a grayscale image pyramid,and composite feature points including SIFT features are extracted.The RANSAC(random sample consensus)algorithm is used to select feature points to calculate the global homography matrix for image registration.Then,an energy function based on local neighbor-hood windows is proposed,and the dynamic programming idea is introduced to use the information entropy maximum point as the starting point for seam search to complete the stitching.The experimental results show that the feature extraction al-gorithm in this paper improves by an average of 122.6％,61.8％,and 3.75％compared to the common SIFT,SURF,and ORB algorithms on the self-made and public dataset UDIS-D.The algorithm in this paper has improved the PSNR,SSIM in-dicators,and visual effects of the stitching results compared to the comparison algorithm.
万方数据
维普
