A New Scheme for Multisensor Image Matching

DOI

10.2991/meici-16.2016.64How to use a DOI?

Keywords

Lteration; Projective transformation; Affine transformation; Nonlinear representation

Abstract

A new iteration scheme for infrared and visible image matching is presented in this paper. The goal is to derive a new method for highly accurate matching of multisensor images. The existing matching algorithms based on image pyramid decomposition have been popular as they have advantages of low computational complexity. However they can only be applied to images from the same sensor. The proposed new iteration approach can register both visible and infrared images. To capture large displacements, coarse-to-fine new refinement of the matching parameters is performed based on the Gaussian pyramid. Parameters are propagated on each round of iteration from a low level to a higher resolution to produce more accurate parameters. Experimental results for matching of infrared and visible images show that the proposed scheme is effective and reliable..

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hailong Wang
AU  - Shuqin Zhang
PY  - 2016/09
DA  - 2016/09
TI  - A New Scheme for Multisensor Image Matching
BT  - Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
PB  - Atlantis Press
SP  - 303
EP  - 307
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-16.2016.64
DO  - 10.2991/meici-16.2016.64
ID  - Wang2016/09
ER  -