A novel image fusion method using IKONOS satellite images

In satellite remote sensing, spatial resolutions of multispectral images over a particular region can be enhanced using better spatial resolution panchromatic images for the same region by a process called image fusion, or more generally data fusion. A fusion method is considered successful, if the spatial detail of the panchromatic image is transferred into the multispectral image and the spectral content of the original multispectral image is preserved in the fused product. This research proposes a novel image fusion algorithm which takes aim at producing both spatially enhanced and spectrally appealing fused multispectral images. In the proposed method, first an intermediary image is created using original panchromatic and multispectral images. This intermediary image contains the high frequency content of the panchromatic source image such that it is the one closest to the given multispectral source image (upsampled) by a natural semi inner product defined. The final fused image is obtained by applying a function which performs convex linear combination of the intermediary image and the upsampled multispectral image. The function used depends on the local standard deviations of the source images. To test the performance of the method, the images from IKONOS sensor are fused using the Brovey, IHS, PCA, wavelet transform based methods, and the proposed method. Both visual and quantitative evaluation results indicate that the proposed method yields to both spectrally and spatially appealing results as the wavelet transform based method, and it gives a better performance when both spatial detail enhancement and spectral content preservation in the fused products are considered. It is also obvious that the method has a potential to get better results if a better fitting, more complex function is found.