Pan-Sharpening Using an Adaptive Linear Model

In this paper, we propose an algorithm to synthesize high-resolution multispectral images by fusing panchromatic (Pan) images and multispectral (MS) images. The algorithm is based on an adaptive linear model, which is automatically estimated by least square fitting. In this model, a virtual difference band is appended to the MS to guarantee the correlation between the Pan and MS. Then, an iterative procedure is carried out to generate the fused images using steepest descent method. The efficiency of the presented technique is tested by performing pan-sharpening of IKONOS, Quick Bird, and Landsat-7 ETM+ datasets. Experimental results show that our method provides better fusion results than other methods.