Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/57515
Title: A novel hyperspectral anomaly detection algorithm for real-time applications with push-broom sensors
Authors: Horstrand, Pablo
Díaz Martín, María 
Guerra Hernández, Raúl Celestino 
López Suárez, Sebastián 
López Feliciano, José Francisco 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Anomaly detection (AD)
Hyperspectral imagery
Onboard processing
Push-broom sensor
Unmanned aerial vehicle (UAV)
Issue Date: 2019
Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 
Abstract: Most practical hyperspectral anomaly detection (AD) applications require real-time processing for detecting complex targets from their background. This is especially critical in defense and surveillance domains, but also in many other scenarios, in which a rapid response is mandatory to save human lives. Dealing with such a high dimensionality of data requires the conception of new algorithms to ease the demanding computing performance. Push-broom scanning represents the mainstream in hyperspectral imaging, introducing added complexity to the equation as there is no information of future pixels. In this paper, a novel technique named line-by-line anomaly detection (LbL-AD) algorithm, is presented as a way of performing real-time processing with a push-broom sensor. The sensor has been mounted on an unmanned aerial vehicle, and the acquired images, together with others from the scientific literature and synthetic ones, have been used to extensively validate the proposed algorithm in terms of accuracy, based on different metrics and processing time. Comparisons with state-of-the-art algorithms were accomplished in order to evaluate the goodness of the LbL-AD, giving as a result an outstanding performance.
URI: http://hdl.handle.net/10553/57515
ISSN: 1939-1404
DOI: 10.1109/JSTARS.2019.2919911
Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing [ISSN 1939-1404]
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