A New Method for Image Fusion Based on Principal Component Analysis and Wavelet Transforms
A New Method for Image Fusion Based on Principal Component Analysis and Wavelet Transforms
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发表时间：
2005
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通讯作者：
Jiang Nian-de;W. Yao-nan
中科院分区：
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作者：
Jiang Nian-de;W. Yao-nan
针对低分辨率多光谱图像和高分辨率全色图像的融合问题，提出了一种基于主成分分析（PCA）和小波变换（WT）的图像融合方法，首先对多光谱图像进行PCA变换，然后对多光谱图像和高分辨率全色图像的第一主成分进行WT变换，通过多分辨率小波分解，利用成像强度的对比，可以将高分辨率全色图像近似融合到多光谱图像近似中，然后对融合后的图像进行小波逆变换重构，并替换多光谱图像的第一主成分，最后，实验结果表明，该方法的融合效果优于IHS变换融合方法、PCA变换融合方法该方法不仅较好地保留了原始多光谱图像的光谱信息，而且增强了图像的空间细节信息。
In this paper,a new method of image fusion method was proposed based on principal component analysis(PCA) and wavelet transforms(WT) to fuse a low-resolution multi-spectral image and high-resolution panchromatic image.Firstly,the multi-spectral image is transformed with PCA.Then,the first principal component of multi-spectral image and high-resolution panchromatic image were transformed by WT,respectively.The high-resolution panchromatic image approximation can be merged into the multi-spectral image approximation using antitheses of imaging intensity by means of multi-resolution wavelet decomposition,and then the merged image is reconstructed by inverse wavelet transform and replaces the first principal component of multi-spectral image.Finally,the fusion image is obtained by taking the inverse PCA transform.The experiment indicates that the performance of new method is better than those of IHS transform-based fusion method,PCA transform-based one,and WT transform-based one.It not only preserves spectral information of the original multi-spectral image well,but also enhances spatial detail information.