Panoramic image generation with lens distortions
Myung-Ho Ju, Hang-Bong Kang · 2013
In this paper, we propose a new method to compensate for lens distortion in image stitching. Lens distortions that arise from the nonlinearity of a lens are the main causes 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. Our experimental results show that the proposed method can efficiently and accurately estimate the distortion factors, and result in a more accurate stitched image than other previous methods based on estimated lens distortion factors.