Stitching Images with Arbitrary Lens Distortions
Myung-Ho Ju, Hang-Bong Kang · International Journal of Advanced Robotic Systems · 2014
In this paper, we propose a new method to compensate for lens distortions in image stitching. Lens distortions that arise from the nonlinearity of a lens are the main cause for mismatches in stitching images. We estimate the distortion factors for each image using the Division Model and linearize the projected relationships between matching distorted feature points. Because our method works at the RANSAC stage, the estimated distortion factors are further refined during the bundle adjustment phase and thus accurate distortion factors are obtained. Applications based on estimated lens distortion factors show that our method is more efficient and that the stitched results are more accurate than other previous methods.