Hyperspectral Image

Hyperspectral imaging (HSI) captures detailed spectral information across numerous bands, enabling precise material identification and scene analysis beyond the capabilities of traditional RGB or multispectral imaging. Current research heavily focuses on improving HSI classification and reconstruction using advanced deep learning architectures, such as transformers and state-space models (SSMs), often incorporating spatial context and addressing challenges like computational efficiency and data scarcity through techniques like self-supervised learning and test-time training. These advancements have significant implications for diverse fields, including remote sensing, precision agriculture, medical imaging, and environmental monitoring, offering enhanced capabilities for material identification, object detection, and scene understanding.