Fusion of QuickBird Multi-sensor Images using Different Techniques

Earth observation satellites such as QuickBird provide panchromatic (PAN) images at high spatial resolution and multispectral (MS) images at high spectral resolution but low spatial resolution. Actually, due to sensor limitations and technical restrictions the instruments are not capable of directly providing an image with high spatial and spectral resolutions. The most efficient and economic way to produce high spatial resolution MS images is by applying image fusion techniques to merge the high spatial information of the PAN image with the high spectral information of the MS image. This paper describes and examines six of the most widely used fusion techniques to merge two sets of QuickBird PAN and MS images covering agricultural and urban areas in Tanta and Alexandria cities, Egypt. The applied fusion techniques utilize different spectral and spatial transformations, they are (1) Intensity-Hue-saturation (IHS), (2) Principle Component Analysis (PCA), (3) High Pass Filter (HPF), (4) Mallat Wavelet Addition (MWA), (5) IHS with Area Model (IHS+Area), and (6) University of New Brunswick fusion model (UNB).  The purpose of this study is to evaluate and compare the spectral and spatial qualities of the fused images due to applying different fusion techniques. The fused images are compared visually and statistically to the original PAN and MS images. The results revealed that the (IHS+Area) method has considerably improved the spectral quality while preserving the spatial information of the original PAN image. However, the improvement of the spectral quality due to applying a certain technique means the deterioration of its spatial quality. Thus, the selection of an appropriate fusion technique depends mainly on the application requirements