BACKGROUND Recently, sparse unmixing has been successfully applied to spectral mixture analysis of remotely sensed hyperspectral images. Based on the assumption that the observed image signatures can be expressed in the form of linear combinations of a number of pure spectral signatures known in advance, unmixing of each mixed pixel in the scene is to find an optimal subset of signatures in a v...

Polarization adds another dimension to the spatial intensity and spectral information typically acquired in remote sensing. Polarization imparted by surface reflections contains unique and discriminatory signatures which may augment spectral target-detection techniques. Benefits such as improving man-made object detection are often touted, as well as possible improvements to spectral algorithms...

In this paper, we propose an approach for automatic generation of novel intrusion signatures. This approach can be used in the signature-based Network Intrusion Detection Systems (NIDSs) and for the automation of the process of intrusion detection in these systems. In the proposed approach, first, by using several one-class classifiers, the profile of the normal network traffic is established. ...

Abstruct-Most applications of hyperspectral imagery require processing techniques which achieve two fundamental goals: 1) detect and classify the constituent materials for each pixel in the scene; 2) reduce the data volumeldimensionality, without loss of critical information, so that it can be processed efficiently and assimilated by a human analyst. In this paper, we describe a technique which...

The classiication of High Range Resolution (HRR) radar signatures using multi-scale features is considered. We present a hierarchical autoregressive moving average (ARMA) model for modeling HRR radar signals at multiple scales, and use spectral features extracted from the model for classifying radar signatures. First, we show that the radar signal at a diierent scale follows an ARMA process if ...

This article proposes a technique for position disambiguating of mobile robots using laser and geomagnetic signatures in indoor terrains. Referring to the geomagnetic signature, magnetic field disturbances are used as unique recognition signatures. First, we gather information about the magnetic heading and the laser mapping as our robot traverses a path between start and goal points of the wor...