A Framelet-Based Iterative Pan-Sharpening Approach

Abstract

Pan-sharpening is used to fuse multispectral images and panchromatic images to produce a multispectral image with high spatial resolution. In this paper, we design a new iterative method based on framelet for pan-sharpening. The proposed model takes advantage of the upsampled multispectral image and a linear relation between the panchromatic image and the latent high-resolution multispectral image. Since the sparsity of the pan-sharpened image under a B-spline framelet transform is assumed, we regularize the model by penalizing l 1 norm of a framelet based term. The model is solved by a designed algorithm based on alternating direction method of multipliers (ADMM). For better performance, we propose an iterative strategy to pick up more spectral and spatial details. Experiments on four datasets demonstrate that the proposed method outperforms several existing pan-sharpening methods.