This paper reviews well-known classic algorithms and more recent experimental
approaches for distinguishing the weak signal of a target (either known or anomalous) from …

Hyperspectral imagery can obtain hundreds of narrow spectral bands of ground objects. The
abundant and detailed spectral information offers a unique diagnostic identification ability for …

Anomaly detection is playing an increasingly important role in hyperspectral image (HSI)
processing. The traditional anomaly detection methods mainly extract knowledge from the …

Anomaly detection is a fundamental task in hyperspectral image (HSI) processing. However,
most existing methods rely on pixel feature vectors and overlook the relational structure …

Most existing techniques consider hyperspectral anomaly detection (HAD) as background
modeling and anomaly search problems in the spatial domain. In this article, we model the …

Hyperspectral anomaly detection (AD) is an important problem in remote sensing field. It can
make full use of the spectral differences to discover certain potential interesting regions …

Anomaly detection has been an important topic in hyperspectral image analysis. This
technique is sometimes more preferable than the supervised target detection because it …

Seismic weak responses from subsurface small-scale geologic discontinuities or
inhomogeneities are encoded in 3D diffractions. Separating weak diffractions from a strong …

Reed–Xiaoli detector (RXD) is recognized as the benchmark algorithm for image anomaly
detection; however, it presents known limitations, namely the dependence over the image …

The low-rank and sparse decomposition model has been favored by the majority of
hyperspectral image anomaly detection personnel, especially the robust principal …