Multiresolution-based image fusion with additive wavelet decomposition

TLDR

Standard fusion methods can distort multispectral spectra when merging high‑resolution panchromatic with low‑resolution multispectral images. The study proposes a multiresolution wavelet‑based technique to fuse high‑resolution panchromatic and low‑resolution multispectral images. The method adds high‑order wavelet coefficients from the panchromatic image to the multispectral intensity component using the a trous algorithm, enabling efficient merging of SPOT and LANDSAT/TM images. Adding high‑order wavelet coefficients to the multispectral intensity component yields superior preservation of spectral and spatial information compared to standard IHS/LHS mergers.

Abstract

The standard data fusion methods may not be satisfactory to merge a high-resolution panchromatic image and a low-resolution multispectral image because they can distort the spectral characteristics of the multispectral data. The authors developed a technique, based on multiresolution wavelet decomposition, for the merging and data fusion of such images. The method presented consists of adding the wavelet coefficients of the high-resolution image to the multispectral (low-resolution) data. They have studied several possibilities concluding that the method which produces the best results consists in adding the high order coefficients of the wavelet transform of the panchromatic image to the intensity component (defined as L=(R+G+B)/3) of the multispectral image. The method is, thus, an improvement on standard intensity-hue-saturation (IHS or LHS) mergers. They used the "a trous" algorithm which allows the use of a dyadic wavelet to merge nondyadic data in a simple and efficient scheme. They used the method to merge SPOT and LANDSAT/sup TM/ images. The technique presented is clearly better than the IHS and LHS mergers in preserving both spectral and spatial information.