Abstract—This paper addresses two issues related to the detection of hyperspectral anomalies. The first issue is the evaluation of anomaly detector ...

This paper addresses two issues related to the detection of hyperspectral anomalies. The first issue is the evaluation of anomaly detector performance even ...

This paper addresses two issues related to the detection of hyperspectral anomalies. The first issue is the evaluation of anomaly detector performance even ...

This paper addresses two issues related to the detection of hyperspectral anomalies. The first issue is the evaluation of anomaly detector performance even ...

ABSTRACT. Recently anomaly detection (AD) has become an important application for target detection in hyperspectral remotely sensed images.

Guo et al. Weighted-RXD and linear filter-based RXD: improving background statistics estimation for anomaly detection in hyperspectral imagery. IEEE Trans ...

Mar 10, 2022 · This algorithm divides the HSI into a background information part and binary classification problem to be detected, which solves the problem of ...

Oct 16, 2024 · Secondly, we enhance background purity by merging pixels close to anomaly-free regions. Moreover, we design a local MD (LMD) algorithm to better ...

Anomaly detection methods in general estimate the spectra of the background (locally or globally) and then detect anomalies as pixels with a large spectral ...

In addition, this paper presents the most comprehensive comparative analysis to-date in hyperspectral anomaly detection by evaluating 22 algorithms on 17 ...