Hyperspectral Semantic Segmentation

Hyperspectral semantic segmentation refers to the pixel-level classification of the entire hyperspectral image cube to identify and distinguish different land cover categories. This task aims to extract detailed semantic information from hyperspectral data, providing high-precision image analysis support for precision agriculture, environmental monitoring, urban planning, and other fields. Unlike hyperspectral image classification, which focuses on the overall scene category label, semantic segmentation is concerned with the classification results of each pixel in the image.