Image Stitching With Manifold Optimization

Abstract

Image stitching usually relies on spatial transformations to do the overlap alignment and distortion mitigation. This paper presents a novel manifold optimization method to seek for the optimal transformations. Especially, the transformations involved in the stitching are treated as elements of a prescribed matrix manifold. Then, the spatially varying homographies are computed by efficient second-order minimization (ESM) on the geometric error of aligning feature correspondences, but with their intrinsic manifold parameterization. To mitigate the distortion, the interpolation between homography and similarity transformation is performed on a general matrix manifold. These on-manifold operations improve the stitching quality with less artifacts of ghosting and distortion. The experiments show the effectiveness of our manifold optimization for image stitching.