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 …

Due to unavailability of prior knowledge about anomalies, background suppression (BS) is a
crucial factor in anomaly detection (AD) evaluation. The difficulty in dealing with BS arises …

Hyperspectral sensors are passive instruments that record reflected electromagnetic
radiation in tens or hundreds of narrow and consecutive spectral bands. In the last two …

As one of the most active research hotspots in hyperspectral remote sensing, anomaly
detection is widely used because it takes effect without any priori information about the …

In this article, a new subspace selection-based discriminative forest (SSDF) method is
proposed for the anomaly detection of hyperspectral remote sensing imagery. Most of the …

Hyperspectral imaging can provide narrow bands and continuous spectrum information.
However, hyperspectral image data have the characteristics of high dimensionality, rich …

In hyperspectral anomaly detection, anomalies are rare targets that exhibit distinct spectral
signatures from the background. Thus, anomalies are with low probabilities of occurrence in …

We propose a sequential nonparametric test for detecting a change in distribution, based on
windowed Kolmogorov–Smirnov statistics. The approach is simple, robust, highly …

The generalized likelihood ratio test (GLRT) is here combined with the nonparametric
approach to derive a new adaptive detector for subpixel targets in hyperspectral images …

高光谱遥感影像数据具有高维特征, 信息冗余, 不确定性显著, 小样本, 空谱合一等特征,
对其进行数据处理面临巨大挑战, 高光谱遥感影像降维是高光谱遥感的重要研究方向之一 …