Pansharpening With Matting Model

Abstract

Pansharpening aims at creating a fused image of high spatial and spectral resolutions through merging a panchromatic (PAN) image with a multispectral (MS) image. Component substitution is the most widely used pansharpening method. However, most research in this field focuses on improving the existing component substitution-based pansharpening methods, e.g., principal component substitution and intensity hue saturation transform. The major contribution of this paper is a novel component substitution framework based on an image matting model. The matting model refers to an MS image that can be decomposed into three components, i.e., alpha channel, spectral foreground, and background. Through substituting the alpha channel of the MS image with the PAN image, the high-resolution MS image is able to be reconstructed perfectly. Experiments performed on different data sets demonstrate that the proposed method outperforms several state-of-the-art pansharpening methods in terms of subjective and objective evaluation.