Fusion technique for SAR and Gray Visible Image based on Hidden Markov Model in Non-subsample Shearlet Transform Domain

DOI

10.2991/icismme-15.2015.165How to use a DOI?

Keywords

Non-subsample Shearlet Transform; Hidden Markov Tree; Image Fusion.

Abstract

To exact the more directional information and important detail information from the images effectively, a novel image fusion algorithm for SAR and gray visible image based on the Hidden Markov Model in the Non-subsample Shearlet Transform (NSST) domain is proposed. In NSST domain, the low frequency coefficients are fused by standard deviation. Meanwhile, the NHMT model is built to train the high frequency coefficients. After that, the energy of gradient is used to select the trained coefficients. Then, the low frequency and high frequency images are fused by inverse transformation of NSST to get the final image. Finally, the simulation proves that compared with other mufti-scale HMT models and traditional NSST fusion strategy, the proposed method in this paper can promote the fusion quality and enhance the information of the images, reducing noise as well.

Copyright

© 2015, 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  - Jian Liu
AU  - Yingjie Lei
AU  - Yaqiong Xing
AU  - Chuanguo Lu
PY  - 2015/07
DA  - 2015/07
TI  - Fusion technique for SAR and Gray Visible Image based on Hidden Markov Model in Non-subsample Shearlet Transform Domain
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 788
EP  - 792
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.165
DO  - 10.2991/icismme-15.2015.165
ID  - Liu2015/07
ER  -