Spatial and Spectral Anisotropic Tensor Total Variation-Driven Adaptive Pansharpening

This letter proposed a spatial and spectral anisotropic tensor total variation (SSATTV)-driven adaptive pansharpening model for the fusion of low-resolution (LR) multispectral (MS) and panchromatic (Pan) images to the high-resolution (HR) MS images. Except for the local spectral consistency constraint-based fidelity term between HR and LR MS used for spectral preservation, the proposed model reformulated the adaptive linear constraint-based fidelity term between Pan and HR MS with the tensor-representation modeling, particularly proposed an SSATTV prior term which imposed the spatial anisotropic TV prior between HR MS and Pan for spatial gradient feature preservation, and the spectral TV sparsity prior on HR MS for further spectral feature preservation. Furthermore, the proposed model was efficiently solved via the alternating direction method of multipliers (ADMM) scheme. Specifically, the experiments validated the superiority of the proposed SSATTV method.

Automated summary

This letter proposes an adaptive pansharpening model for the fusion of multispectral and panchromatic images, incorporating spatial and spectral anisotropic tensor total variation for spatial gradient and spectral feature preservation.