Remote sensing image fusion based on PCA transform and wavelet transform

The traditional PCA image fusion can produce multi-spectral image information variable loss in remote image fusion. Aim to it, a new algorithm of remote sensing image fusion based on PCA and wavelet transform was proposed in this paper. Firstly, principal component transformation for multi -spectral image was performed by eigenvalues and eigenvectors in each wave band. Secondly, the first non principal component of non-gray image and multi spectral image were matched in histogram information. Finally, inverse PCA transform was carried out for three principal components to obtain the desired fusion image. Experimental results show the proposed algorithm does not only maintain multi spectral information but also enhanced the processed image details, and the processed image has better subjective visual effect and objective quantitative indicators.