The aim of PAN-sharpening is to fuse a Multispectral (MS) image and a Panchromatic (PAN) image into a High-Resolution Multispectral (HRMS) image. The spatial resolution of the HRMS image is extracted from the PAN image, while the spectral resolution is extracted from the MS image. In this paper, a PAN-sharpening model based on the gradient constraint and Laplacian regularization is proposed. The objective function, which is a convex optimization problem, aims to minimize three least-square terms: (1) spectral constraint, (2) spatial constraint, and (3) image regularization. In experiments, the proposed method not only demonstrates better visual quality but also shows improvement in many quality metric evaluations.
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