Open AccessRobust registration for ultra-field infrared and visible binocular images
Author(s) -
Shuai Zhang,
Fuyu Huang,
Bingqi Liu,
Gang Li,
Yichao Chen,
Liankun Sun,
Yunzuo Zhang
Publication year - 2020
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.391672
Subject(s) - artificial intelligence , computer vision , computer science , phase congruency , image registration , histogram , epipolar geometry , optics , pattern recognition (psychology) , feature extraction , image (mathematics) , physics
The ultra-field infrared and visible image registration is a challenging task due to its nonlinear imaging and multi-modal image features. In this paper, a robust registration method is proposed for the ultra-field infrared and visible images. First, control points are extracted utilizing phase congruency and optimized based on the guidance map, which is proposed according to significant structures information. Second, ROI pair matching is accomplished based on epipolar curve. Its effect is equivalent to a search window that is popular in methods with the standard field of view, and it can overcome the content differences in the search window caused by nonlinear imaging and vision disparity. Third, a descriptor, named multiple phase congruency directional pattern (MPCDP), is established and composed of distribution information and main direction. The phase congruency amplitudes are encoded as binary patterns, and then they are represented as weighted histogram for distribution information. Six pairs of ultra-field infrared and visible images are employed for registration experiments, and the results demonstrate that the performance of the proposed is robust and accurate in five types of ultra-field scenes and two different camera relationships.