Adaptive dual-feature image stitching based on moving-DLT
Mowen Xue, Xudong Li, Hongzhi Jiang, Huijie Zhao · Optical Sensing and Imaging Technologies and Applications · 2018
Image stitching is to create a wider viewing angle image with high quality from a series of images which have overlapping regions. It is one of the most important fields of image processing. The traditional global homography method, such as AutoStitch, will be invalid when the scene is not planar or the views differ not purely by rotation. The local homography warping method, which is based on the grid optimization algorithm, such as as-projective-as-possible(APAP) warping can get a better result relative to global homography method, but it deeply relies on the quality and quantity of matching points. In this paper, a new method for low texture scene stitching was proposed which combines point features and line features to compute local warping matrix. So the method can get enough features in low texture region. Our results are compared with APAP and AutoStitch method. The results show that our method have less ghosting and deformation.