基于Contourlet系数局部特征的选择性遥感图像融合算法

为了使融合后的多光谱图像在显著提高空间分辨率的同时,尽可能多地保持原始多光谱特性,提出了一种基于Contourlet变换系数局部特征的选择性遥感图像融合方法。根据多光谱和全色图像融合过程中Contourlet变换后的低频和高频部分融合目的的不同,对得到的近似和各层各方向的细节分量分别运用窗口邻域移动模板逐一计算相应区域Contourlet系数阵的不同局部特征量,然后选择适当的准则,对图像的近似和细节分量分别应用不同的策略在Contourlet系数域内进行选择性融合,通过Contourlet和亮度-色调-饱和度(IHS)逆变换得到融合的高分辨率多光谱图像。采用Landsat TM多光谱和SPOT全色图像进行的融合实验结果表明:提出的算法在显著提高空间分辨率的同时,又能很好地保持原始图像的光谱特征,并优于传统的融合方法。

Selective Remote Sensing Image Fusion Method Based on the Local Feature of Contourlet Coefficients

In order to remarkably improve the spatial resolution of the fused multispectral images and preserve the original multispectral characteristics as much as possible,a selective remote sensing image fusion method is proposed based on the local feature of contourlet coefficients.Firstly,a window neighborhood mobile template is used to calculate the different local features of corresponding contourlet coefficient matrix one by one for the approximate components and the detail components of each direction of each layer resulting from contourlet transform according to the different fusion purposes of low and high frequency parts in the fusion process of multi-spectral and panchromatic images.Then the approximate images and detail images are fused selectively in contourlet coefficients domain by applying different fusion rules based on proper criterion.The resultant image with high resolution and multi-spectral characteristics is obtained by inverse contourlet transform and inverse intensity-hue-saturation(IHS) transform.Landsat TM and SPOT images are used to conduct the fusion experiment and the results show that the proposed algorithm can remarkably enhance the spatial details and well preserve the spectral features of the original images.This algorithm performs better than traditional fusion methods.