基于小波支持向量回归的遥感多光谱图像分辨率增强算法

利用小波支持向量回归，实现了遥感多光谱图像分辨率的增强。首先采用非下采样Contourlet变换对低分辨率的多光谱图像和高分辨率的全色图像进行多分辨率分解，再利用小波支持向量回归对分解系数进行学习和预测，获得分辨率初步提高的多光谱图像，最后再与传统的插值方法得到的结果进行融合来实现多光谱图像分辨率增强。实验结果表明:此方法借遥感全色图像的辅助获得丰富的高频细节信息，使得分辨率增强结果无论是最小均方误差还是峰值信噪比都要优于仅依靠原图像本身放大的传统方法以及其他的分辨率增强方法。

Resolution Enhance Algorithm for Remote Sensing Multi spectral Image Based on Wavelet Support Vector Regression

Wavelet support vector regression is utilized to enhance the resolution for remote sensing multi spectral image. Firstly, both low resolution multi spectral image and high resolution panchromatic image are decomposed into multi resolution by using nonsubsampled contourlet transform. Then, by using wavelet support vector regression, the decomposed coefficients are learned and predicted so as to obtain multi spectral image with preliminary enhanced resolution. Finally, the above results are further fused with the traditional interpolate one to achieve the resolution enhance of multi spectral image. Experiment results show that the proposed algorithm utilizes the auxiliary of remote sensing panchromatic image to effectively attain a wealth of high frequency detail information, such that either the minimum mean squared error or the peak signal to noise ratio is superior to these from the traditional methods only depending on the amplification of image itself and other resolution enhance methods.