Fusion of multi-spectral image and panchromatic image based on support vector regression |
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Authors: | HU Gen-sheng and LIANG Dong |
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Affiliation: | Key Laboratory of Intelligent Computing and Signal Processing, Ministry of Education, Anhui University, Hefei 230039, China;School of Electronics and Information Engineering, Anhui University, Hefei 230039, China;Key Laboratory of Intelligent Computing and Signal Processing, Ministry of Education, Anhui University, Hefei 230039, China;School of Electronics and Information Engineering, Anhui University, Hefei 230039, China |
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Abstract: | In our study, support vector value contourlet transform is constructed by using support vector regression model and directional filter banks. The transform is then used to decompose source images at multi-scale, multi-direction and multi-resolution. After that, the super-resolved multi-spectral image is reconstructed by utilizing the strong learning ability of support vector regression and the correlation between multi-spectral image and panchromatic image. Finally, the super-resolved multi-spectral image and the panchromatic image are fused based on regions at different levels. Our experiments show that, the learning method based on support vector regression can improve the effect of super-resolution of multi-spectral image. The fused image preserves both high space resolution and spectrum information of multi-spectral image. |
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Keywords: | image processing image fusion support vector regression super-resolution |
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