Freak Descriptor With Spatial Pyramid Kernel For Scene Categorization

DOI

10.2991/meic-15.2015.31How to use a DOI?

Keywords

Spatial Pyramid Kernel; FREAK; Sift; Scene Categorization; SVM

Abstract

In order to solve the problem of spectral distortion and the fuzzy texture in visible and infrared image fusion technology, a novel visible and infrared image fusion method based on the Nonsubsampled Contourlet Transform (NSCT) and Pulse Coupled Neural Networks (PCNN) is proposed in this paper. First, we gain three components of visible image, luminance I, chrominance H and saturation S, using the IHS transform. Then, we gain three coefficients, low frequency sub-band, passband sub-band and high frequency coefficient by decomposing the component I and infrared image with the help of the NSCT. Next, we use weighted-sum method to fuse the low frequency sub-band and PCNN method to fuse the other sub-band coefficient respectively. At last, we gain the fusion image by using the inverse IHS transform on the fusion component I gained by the inverse NSCT transform. Experiments show that our method have better fusion quality and can be more better to keep the visible spectral and detail information than some traditional methods such as, Laplace method, Wavelet method and Lifting Wavelet method.

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  - Qiong Yao
AU  - Xiang Xu
PY  - 2015/04
DA  - 2015/04
TI  - Freak Descriptor With Spatial Pyramid Kernel For Scene Categorization
BT  - Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 126
EP  - 129
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-15.2015.31
DO  - 10.2991/meic-15.2015.31
ID  - Yao2015/04
ER  -