COLOUR-BASED AND CRITERIA-BASED METHODS FOR IMAGE FUSION

Panchromatic and multispectral images are useful for the acquisition of geospatial information about the Earth surface for the assessment of land resources and environment monitoring. Panchromatic images usually have a better spatial resolution than the multispectral ones of the same sensor, while the multispectral images provide spectral properties of the objects. Image fusion methods are needed to find the missing spatial details in the multispectral images using the panchromatic ones and transfer these details into the multispectral images without or with limited spectral content distortion. This study addresses two classes of image fusion approaches: colour-based methods and statistical methods. Specifically, the traditional RGB to IHS transform is generalized from 3-D to n-D such that it can handle multiple image bands. As for the statistical methods, we propose a criteria-based approach that produces fusion products to meet a set of predefined desired properties. Principles, solutions, and formulation regarding these two approaches are presented. The proposed methods are tested with QuickBird images. Fusion results are evaluated visually and quantitatively with discussions on their properties