GreenWarps: A Two-Stage Warping Model for Stitching Images Using Diffeomorphic Meshes and Green Coordinates

Abstract

Image Stitching is a hard task to solve in the presence of large parallax in the images. Specifically, for a sequence of frames from unconstrained videos which are considerably shaky, recent works fail to align such a sequence of images accurately. The proposed method “GreenWarps” aims to accurately align frames/images with large parallax. The method consists of two novel stages, namely, Prewarping and Diffeomorphic Mesh warping. The first stage warps unaligned image to the reference image using Green Coordinates. The second stage of the model refines the alignment by using a demon-based diffeomorphic warping method for mesh deformation termed “DiffeoMeshes”. The warping is performed using Green Coordinates in both the stages without the assumption of any motion model. The combination of the two stages provide accurate alignment of the images. Experiments were performed on two standard image stitching datasets and one dataset consisting of images created from unconstrained videos. The results show superior performance of our method compared to the state-of-the-art methods.