Fusion of Panchromatic and Multispectral Images by Genetic Algorithms

Pan-sharpened MS is a fusion product in which the multispectral (MS) bands are spatially enhanced by the higher-resolution panchromatic (Pan) image. Most effective algorithms for pan-sharpening are based on multiresolution analysis (MRA), e.g., wavelets, Laplacian pyramids, wavelet frames, or curvelets. MRA approaches present one main critical point: filtering operations may produce ringing artifacts when high frequency details are extracted from the panchromatic image. In this paper, a pan-sharpening algorithm for 4-band MS data is proposed, which is not based on MRA, but it applies a Generalized Intensity-Hue-Saturation (GIHS) transformation to the MS bands. A genetic algorithm is adopted to define the injection model which establishes how the missing highpass information is extracted from the Pan image. The fitness function of the genetic algorithm which provides the algorithm parameters driving the fusion process is based on a quality index specifically designed for quality assessment of,4-band MS images. Both visual and objective comparisons with advanced fusion methods are presented on QuickBird image data.