Dual-correlation transformation for image stitching
Jiajie Wang, Guohua Gu, Minjie Wan, Kan Ren · Journal of Electronic Imaging · 2018
In order to obtain accurate and stable image stitching results, we propose a stitching method for two images captured from different viewpoints based on correlation transformation. Aiming at resolving the limitation of the projective transformation that is commonly used in image stitching, a transformation called dual-correlation transformation is proposed in this paper. First, the estimation result of the fundamental matrix is calculated by the direct linear transformation based on the corresponding points in two images. Second, according to the presented dual-correlation transformation, a pair of correlation transformation matrices that are needed for dual-correlation warp can be obtained to realize the correspondence of each pixel in different images. Up to this stage, the method of image stitching based on transformation matrices has been accomplished. Finally, an optimization method based on factorization is especially proposed to solve the discontinuity problem that may occur in the dual-correlation warp. The experimental results and analyses show that the proposed method can achieve more accurate and natural stitching effects and has less computing time of the images in separate scenes compared with other similar methods.