A High-Order Statistical Tensor Based Algorithm for Anomaly Detection in Hyperspectral Imagery

A High-Order Statistical Tensor Based Algorithm for Anomaly Detection in Hyperspectral Imagery

Recently, high-order statistics have received more and more interest in the field of hyperspectral anomaly detection. However, most of the existing high-order statistics based anomaly detection methods require stepwise iterations since they are the direct applications of blind source separation. Moreover, these methods usually produce multiple detection maps rather than a single anomaly distrib...

Parallel Computing of High Order Anomaly Detection in Hyperspectral Imagery

Anomaly detection is to detect small targets with unknown and distinct spectrum from the background. For hyperspectral images with hundreds of co-registered bands, it is a great challenge to search for small targets in this huge amount of data. A previously proposed anomaly detection algorithm based on high-order statistics has been proved to be an effective method for surveillance problems. Si...

3D Gabor Based Hyperspectral Anomaly Detection

Hyperspectral anomaly detection is one of the main challenging topics in both military and civilian fields. The spectral information contained in a hyperspectral cube provides a high ability for anomaly detection. In addition, the costly spatial information of adjacent pixels such as texture can also improve the discrimination between anomalous targets and background. Most studies miss the wort...

Innovative Statistical Inference for Anomaly Detection in Hyperspectral Imagery

Kernel-Based Anomaly Detection in Hyperspectral Imagery

In this paper we present a nonlinear version of the wellknown anomaly detection method referred to as the RXalgorithm. Extending this algorithm to a feature space associated with the original input space via a certain nonlinear mapping function can provide a nonlinear version of the RX-algorithm. This nonlinear RX-algorithm, referred to as the kernel RX-algorithm, is basically intractable mainl...