Abstract
This paper describes a new method for predicting the detectability of thin gaseous plumes in hyperspectral images. The novelty of this method is the use of basis vectors for each of the spectral channels of a collection instrument to calculate noise-equivalent concentration-pathlengths instead of matching scene pixels to absorbance spectra of gases in a library. This method provides insight into regions of the spectrum where gas detection will be relatively easier or harder, as influenced by ground emissivity, temperature contrast, and the atmosphere. Our results show that data collection planning could be influenced by information about when potential plumes are likely to be over background segments that are most conducive to detection.
Highlights
The value of hyperspectral imagery in detecting evidence of thin gaseous plumes is dependent upon the ability of the analysis tools to detect those materials when they are present
In this paper we extend the application of basis vectors (BV) to estimate the noise-equivalent concentration-pathlength (NECL) for pixels in an image or image segment, relate the NECL to the signal-to-noise ratio (SNR) for an image or image segment, and estimate the minimum detectable concentration-pathlength (MDCL) for gases that have a single dominant spectral peak
We presented a method for predicting the detectability of thin gaseous plumes in hyperspectral images
Summary
The value of hyperspectral imagery in detecting evidence of thin gaseous plumes is dependent upon the ability of the analysis tools to detect those materials when they are present. Very often the approach is to evaluate specific gases over specific backgrounds and temperature emissivity (TE) contrasts The difficulties with this approach for mission planning is that small gas libraries result in efficient searching but risk missed detections because member gases may not cover all the gases in the image. Their results show that applying a whitened-matched filter to each BV in succession will identify spectral channels with anomalous activity The library in this case is the set of BVs that correspond to each spectral channel and is defined by the resolution and bandwidth of the image. This approach is useful for detection because it spans the full spectral dimension of the image and is agnostic to individual gas characteristics, resolving the issue of missed detections because of mismatches between image gases and library members. Extension of these results to gases with multiple peaks warrants further research
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
