Advanced Spectral Classifiers for Hyperspectral Images: A review

著者: Pedram Ghamisi, Javier Plaza, Yushi Chen, Jun Li, Antonio Plaza - IEEE Geoscience and Remote Sensing Magazine 2017 被引用: 658

Hyperspectral image classification has been a vibrant area of research in recent years. Given a set of observations, i.e., pixel vectors in a hyperspectral image, classification approaches try to allocate a unique label to each pixel vector. However, the classification of hyperspectral images is a challenging task for a number of reasons, such as the presence of redundant features, the imbalance among the limited number of available training samples, and the high dimensionality of the data.