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Hyperspectral image pansharpening for photo analysis by ratio enhancement

Ratio enhancement (RE) methods are typical fusion techniques that have been widely used in multispectral image pansharpening. The construction of a low-resolution Pan image is a crucial step of RE methods. However, it is observed that the existing RE methods cause serious color distortion in HS image pansharpening. This problem arises from the ideal assumptions of Pan and HS images: (i) the relation that exists between Pan and HS bands is linear; (ii) regional variations of Pan and HS images do not have influence on pansharpening results; (iii) the multiple linear regression often fails to obtain the accurate weights of HS bands while the number of HS bands is more than 10. To solve this problem, the original HS bands are reduced to a small amount of synthesized HS bands by an average of neighbor bands, and then the pixels of Pan and HS images are divided into different groups. For each pixel group, the multiple linear regression between Pan and HS bands is utilized to calculate the weights of synthesized HS bands to synthesize a qualified low-resolution Pan image. Finally, the HS image is fused by a ratio enhancement, in which the ratio is obtained by image division between the Pan image and the synthesized Pan image. The experiments on EO-1 data sets demonstrated that the proposed method had a good performance on fusion quality, and outperformed the compared methods.