Temporal-Spectral Detection in Long Wave Infrared Hyperspectral Imagery
Abstract
Ground-based staring hyperspectral chemical detectors allow for repeated measurements through time with near-perfect image registration. The problem with standard spectral based hyperspectral detection algorithms is that they do not make effective use of this temporal information. In this paper we show that significant improvements in detection performance for staring geometry can be made by making use of statistical information obtained from previous samples and new temporal-spectral detection algorithms are developed. These new algorithms have the advantage that they limit detection to regions where both temporally and spectrally significant events have occurred. We discuss the development of these algorithms and demonstrate the performance of both temporal-spectral and spectral detectors for detection of gaseous plumes using data from the FIRST (Field-Portable Imaging Radiometric Spectrometer Technology) passive long wave infrared (LWIR) hyperspectral sensor.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2008
- Accession Number
- ADA482363
Entities
People
- Avishai Ben-david
- Charles E. Davidson
- Daniel C. Heinz
Organizations
- Science and Technology Corporation (United States)