lzw-lzw / Hyperspectral-anomaly-detection-methods

Hyperspectral Anomaly Detection

Hyperspectral anomaly detection methods

These methods are implemented in matlab

papers:

RX:Adaptive Multiple-Band CFAR Detection of an Optical Pattern with Unknown Spectral Distribution

LRX:Analysis and Optimizations of Global and Local Versions of the RX Algorithm for Anomaly Detection in Hyperspectral Data

CRD:Collaborative Representation for Hyperspectral Anomaly Detection

LSMAD:A Low-Rank and Sparse Matrix Decomposition-Based Mahalanobis Distance Method for Hyperspectral Anomaly Detection

LRR:Robust Subspace Segmentation by Low-Rank Representation

LRASR:Anomaly Detection in Hyperspectral Images Based on Low-Rank and Sparse Representation

KIFD:Hyperspectral Anomaly Detection With Kernel Isolation Forest

LSC-TV:Local Spatial Constraint and Total Variation for Hyperspectral Anomaly Detection