Multispectral and Panchromatic image fusion using Spatial PCA

Obtaining an image with high spectral and spatial resolution is the goal of image fusion. PCA is a well-known pan-sharpening approach widely used for its efficiency and high spatial resolution. However, it can distort the spectral characteristics of the multispectral images. To avoid the weak points of the standard PCA technique, spatial PCA transform has been proposed and reasons of superiority of this method in maintaining the spectral information are discussed in this paper. Also, a new assessment criterion is proposed and the advantage of this criterion relative to the conventional mutual information criterion is argued. The proposed assessment metric and other popular metrics such as: ERGAS, SAM, correlation coefficient UIQI, and mutual information are used to analyze the fusion result. These assessments show that the proposed method has the least color distortions and contains more spatial information.