978-620-0-29348-0

Automated Density Estimation in Hyperspectral Anomaly Detection

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Summary:

Detecting targets with unknown spectral signatures in hyperspectral imagery has been proven to be a topic of great interest in several applications. Because no knowledge about the targets of interest is assumed, this task is performed by searching the image for anomalous pixels, i.e. those pixels deviating from a statistical model of the background. In this thesis work, a new scheme is proposed for detecting both global and local anomalies.

Author:

Tiziana Veracini

Biographie:

After I received my Bachelor's and Master's degrees in Telecommunications Engineering, I obtained my PhD degree in Remote Sensing. At the moment, I am System Analyst in IDS. I have developed and designed systems aimed at automatic information retrieval from hyper- and multi-spectral, Infrared and SAR images acquired by satellite or aerial vehicles.

Number of Pages:

144

Book language:

English

Published On:

2019-08-22

ISBN:

978-620-0-29348-0

Publishing House:

LAP LAMBERT Academic Publishing

Keywords:

Remote sensing, adaptive estimation, Hyperspectral imaging, image fusion, image sensors, Probability

Product category:

SCIENCE / Earth Sciences