Pansharpening With Joint Local Low Rank Decomposition and Hierarchical Geometric Filtering

Extracting matched details of the PANchromatic (PAN) image and injecting them into the MultiSpectral (MS) images, is very crucial in pansharpening. In this paper, a new pansharpening method based on Joint Local Low Rank Decomposition (JLLRD) and Hierarchical Geometric Filtering (HGF) is proposed. First, a cascaded geometric filtering is performed on the PAN and MS images, to extract their multi-scale directional details. Then a joint local low rank decomposition is developed to deduce low-rank and sparse components for injection. Finally, an adaptive injection rule based on spectral correlation coefficient, is designed to further reduce spectral distortion of the fused images. Several experiments are taken to investigate the performance of the proposed JLLRD-HGF method, and the results show that it can extract more accurate injection details and produce less spectral and spatial distortions than its counterparts.