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Due to some practical limitations, it is not possible to adopt images which have both high spectral and spatial resolutions. Image fusion is one of the methods that utilizes image supplementary information, to the effect that it combines the spatial information of images with high spatial resolution, By the use of these spectral information of the images with high spectral resolution, one can creates an image that has high spatial and spectral resolutions simultaneously. Current methods and algorithms of image fusion are not efficient enough to combine new satellite images due to some changes in these satellites; therefore, providing new methods of image fusion is of paramount significance for the above-mentioned satellites. Image fusion methods should desirably maintain the spectral and spatial information of the original images. In the present study, a new algorithm was introduced to combine the spatial information of the IKONOS images with the spatial resolution of 1m with the spectral information of the SPOT images with the spatial resolution of 20m. This algorithm is in the feature-level and is based on the Retinal Model. Other existent fusion models such as IHS, HPF, PCA, Wavelet and the hybrid Wavelet-PC were also applied to these images. The results of the spatial and spectral assessments of the combined images indicated that the spectral and spatial information of the proposed method are better. One of the major advantages of this method is that there is no need for resampling, which is a must in other methods.

Keywords: IKONOS, Remote Sensing, Image fusion, Spectral‌ information, ‌ Spatial information, ‌ SPOT

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