Remote Sensing Image Fusion Method Based on improved Radial Basis and Fast partition Interpolation

DOI

10.2991/iccia-16.2016.87How to use a DOI?

Keywords

Compactly supported; Empirical mode decomposition; Wavelet transform; Remote sensing image fusion.

Abstract

A novel algorithm for image fusion based on improved Radial Basis Function named Compactly Supported Radial Basis Function (CSRBF) and fast partition interpolation is proposed. Empirical mode decomposition (EMD) construct the implicit surface for approximating the 3D points set by using RBF for reconstructing smooth surface. Using CSRBF, the matrix of corresponding system of the linear algebraic equations is spare and bounded. So it can decrease the complexity of RBF algorithm. A fast block method enables to improve processing speed. In addition, the paper combines IHS and à trous wavelet transform (AWT) so that spectral information of the original image is reserved and spatial detail of image fusion is enhanced. A number of examples demonstrates that the algorithm is appied to the remote sensing image fusion and obtain good results.

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  - Zhanwei Qu
PY  - 2016/09
DA  - 2016/09
TI  - Remote Sensing Image Fusion Method Based on improved Radial Basis and Fast partition Interpolation
BT  - Proceedings of the 2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016)
PB  - Atlantis Press
SP  - 474
EP  - 480
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-16.2016.87
DO  - 10.2991/iccia-16.2016.87
ID  - Qu2016/09
ER  -