Combined regional homography-affine warp for image stitching
Xinyi Li, Lin He, Xinguo He · 2023
Image stitching is the process of combining multiple images with narrow fields of view into a panoramic image with high resolution. Conventional global warp-based image stitching algorithm has limited alignment accuracy and causes shape distortion while spatially-varying warp-based ones have high computational complexity. To address these problems, we proposed a novel regional warp which adopts various transformation models to handle different areas of the image. Images can be divided into overlapping and non-overlapping regions based on the distribution of matched features. For the overlapping area, two kinds of projective transformation are adopted in combination to warp each pixel in this region. For the non-overlapping area, it is further partitioned into two regions where a projective transformation and an affine transformation are utilized separately. Experimental results show that the proposed warp not only provides good alignment accuracy but also avoids severe shape distortion.