Feature-level Fusion of Dual-band Infrared Images Based on Gradient Pyramid Decomposition

DOI

10.2991/iccsee.2013.571How to use a DOI?

Keywords

image fusion, feature extraction, Gradient pyramid decomposition, image reconstruction

Abstract

Infrared thermal imager has been widely used in the fields of missile guidance and flaw detection. To identify the target clearly, the advanced one adopts dual bands sensors to capture images. Since of that, there is an urgent need of a fusion of the dual-bands images. The fused result includes much more exhaustive information than any single one, and can better reflect the actual. Among the algorithms used to fuse the dual-band infrared images, the weighted algorithm is the most widely used and easiest to be achieved. Nonetheless, its effect is not desired. We extract the features of the source images and make a fuse based on them on the feature-level. To get a better result, in this paper, the fusion strategy based on the Gradient pyramid transform has been mainly adopted. Meanwhile, there is a comparison with the weighted algorithm. Also, it makes an evaluation and analysis to the experimental data, and finally obtains the desired results.

Copyright

© 2013, 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  - Xiujie Qu
AU  - Fu Zhang
AU  - Ying Zhang
PY  - 2013/03
DA  - 2013/03
TI  - Feature-level Fusion of Dual-band Infrared Images Based on Gradient Pyramid Decomposition
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 2279
EP  - 2282
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.571
DO  - 10.2991/iccsee.2013.571
ID  - Qu2013/03
ER  -