Open AccessStitching Images with Arbitrary Lens Distortions
Author(s) -
Myung-Ho Ju,
Hang-Bong Kang
Publication year - 2014
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/57160
Subject(s) - image stitching , ransac , distortion (music) , computer science , lens (geology) , computer vision , artificial intelligence , bundle adjustment , matching (statistics) , feature (linguistics) , image (mathematics) , optics , mathematics , telecommunications , physics , amplifier , linguistics , statistics , philosophy , bandwidth (computing)
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