Image fusion techniques have been developed to utilize different types of image data. The aim of image fusion is to improve the quality of the information by combining two or more different types of images. Pan sharpening is one of the most common fusion techniques used for its efficiency and simplicity. It fuses a cube of multi/hyperspectral image of low spatial resolution with a panchromatic image (PAN) of a higher spatial resolution to obtain an image with high spectral and spatial resolution. This requires a transformation tool to separate the spatial information of the cube from its spectral
information. Some of these transformations include Intensity-Hue-Saturation (IHS), principle component analysis (PCA), wavelet transform (WT) and independent component analysis (ICA). IHS is considered the most popular transformation tool because of its simplicity and efficiency. IHS introduces a fused image of high spatial resolution but it suffers from some spectral distortion. In this paper, we tried to solve this problem by using an adaptive image coefficient and a morphological edge detector with the original IHS transform. From experimental results, depicted in this paper, the
new proposed IHS fusion method produced images of high spatial resolution with minimal spectral distortion compared to the original and adaptive IHS pan sharpening.