An Improved infrared and visible image fusion algorithm based on the Second Generation Curvelet Transform

DOI

10.2991/mce-14.2014.65How to use a DOI?

Keywords

Image Fusion; Multi-resolution Analysis; the Second Generation Curvelet Transform

Abstract

The fusion of infrared images and visible images can combine complementary information in an image, so we can better describe a scene, and it is helpful for some tasks such as target detection, target localization and environment recognition. In this paper, we use the Second Generation Curvelet Transform (SGCT) to decompose infrared images and grayscale visible images to propose a new image fusion algorithm. This algorithm uses a multi-resolution decomposition of different tools and different fusion rules implementation. The simulation results show that, compared with existing algorithms, this algorithm have improved to some extent in the evaluation of fused images.

Copyright

© 2014, 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  - Xiaojun Liu
AU  - Jianyu Wang
PY  - 2014/03
DA  - 2014/03
TI  - An Improved infrared and visible image fusion algorithm based on the Second Generation Curvelet Transform
BT  - Proceedings of the 2014 International Conference on Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 297
EP  - 300
SN  - 1951-6851
UR  - https://doi.org/10.2991/mce-14.2014.65
DO  - 10.2991/mce-14.2014.65
ID  - Liu2014/03
ER  -