Abstract

The main objective of image fusion is to create a new image regrouping the complementary information of the original images. The challenge is thus to fuse these two types of images by forming new images integrating both the spectral aspects of the low resolution images and the spatial aspects of the high resolution images. The most commonly used image fusion techniques are: Principal Components Analysis (PCA), Intensity-Hue-Saturation Transformation (IHS), High Pass Filter (HPF) and Wavelet Transformation (WT). The PCA and IHS, are simple to use but they are highly criticized because the resulting image does not preserve faithfully the colors found in the original images. The HPF method is sensitive to the filtering used (filtering type, filter window size, etc.) and the mathematical operations used. The WT approach is very often reported in the literature, but it's procedure is based on a complex and sophisticated pyramidal transformation where the result also depends on the level of decomposition and the filtering technique used to construct the wavelet coefficients. We present here a new and original method of fusion, capable of (1) Combining a high resolution image with a low resolution image with or without any spectral relationship existing between these two images; (2) Preserving the spectral aspect of the low resolution image while integrating the spatial information of the high resolution image. Compared to existing technologies reported in the literature the new proposed method is an innovative and unique technique in its own right

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