Panchromatic Image

Panchromatic (PAN) image fusion, or pansharpening, aims to enhance the spatial resolution of multispectral (MS) or hyperspectral (HS) imagery by integrating it with high-resolution PAN data. Current research heavily utilizes deep learning, employing architectures like convolutional neural networks (CNNs), neural radiance fields (NeRFs), and state-space models (e.g., Mamba) to achieve superior fusion results, often incorporating techniques like attention mechanisms and generative models. This field is crucial for improving the quality of remote sensing data, enabling more accurate applications in diverse areas such as environmental monitoring, urban planning, and precision agriculture.