基于高阶奇异值分解的多光谱和全色遥感图像融合

Multi-spectral and Panchromatic Remote Sensing Image Fusion Based on Higher Order Singular Value Decomposition

为了使融合图像保留丰富的光谱信息和空间细节信息,本文提出了一种基于高阶奇异值分解的多光谱和全色遥感图像融合方法.该方法首先对多光谱MS图像进行HIS变换,获得亮度分量,并将全色PAN图像与亮度分量进行直方图匹配,然后对全色图像和亮度分量形成的张量图像进行高阶奇异值分解,计算分解系数的结构张量,利用其特征值构造活动测度0,并采用Q取大的融合策略进行融合.实验结果表明,与传统融合方法相比,本文方法的融合结果较好地保留了光谱信息和空间细节信息.

In order to retain rich spectral and spatial detail information,a remote sensing image fusion method based on high order singular value decomposition(HOSVD)is proposed.Firstly,the multi-spectral image is converted to HIS,which produces a luminance component.Then sub-tensor is constructed by two image patches separated from the luminance component and panchromatic image and HOSVD is employed to obtain the decomposition coefficients.Finally,the choose max fusion rule based on activity level is proposed for fusing the decomposition coefficients.Experimental results indicate that the proposed method performs better than traditional methods both in spectral and spatial detail information.