Pan Sharpening

Pan-sharpening integrates high-resolution panchromatic and low-resolution multispectral satellite images to create high-resolution multispectral images, improving the detail and information content for various applications. Current research emphasizes improving both spectral fidelity and spatial enhancement, exploring advanced architectures like transformers and generative adversarial networks (GANs), as well as model-driven approaches incorporating image reasoning priors and iterative refinement techniques. These advancements aim to overcome limitations of existing methods, leading to more accurate and robust pan-sharpening results with improved interpretability, ultimately benefiting remote sensing analysis and related fields.