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Rare Jarosite Detection in CRISM Imagery by Non-Parametric Bayesian Clustering

Dundar, Murat and Ehlmann, Bethany L. (2016) Rare Jarosite Detection in CRISM Imagery by Non-Parametric Bayesian Clustering. In: 2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE , Piscataway, NJ, pp. 1-5. ISBN 9781538605905. http://resolver.caltech.edu/CaltechAUTHORS:20160902-093433840

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Abstract

Discovery of rare phases on Mars is important as they serve as indicators of the geochemistry of the Mars surface and facilitate understanding of mineral assemblages within a geologic unit. Identification of rare minerals in high spatial and spectral resolution Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) visible/shortwave infrared (VSWIR) images has been a challenge due to the presence of both additive and multiplicative noise and other artifacts, affecting all collected images, in addition to the limited spatial extent of regions hosting these minerals. In an effort to automate this task we evaluate various clustering algorithms using the detection of rare jarosite, associated with spectrally similar minerals in CRISM imagery, as a case study. We compare nonparametric Bayesian and standard clustering algorithms and show that a recently developed doubly nonparametric Bayesian model could be effective for this task.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/WHISPERS.2016.8071747 DOIArticle
http://ieeexplore.ieee.org/document/8071747PublisherArticle
http://www.ieee-whispers.comOrganizationConference Website
ORCID:
AuthorORCID
Ehlmann, Bethany L.0000-0002-2745-3240
Additional Information:© 2016 IEEE. This research was sponsored by the National Science Foundation (NSF) under Grant Number IIS-1252648 (CAREER). The content is solely the responsibility of the author and does not necessarily represent the official view of NSF.
Funders:
Funding AgencyGrant Number
NSFIIS-1252648
Subject Keywords:CRISM, jarosite, rare target detection, non-parametric bayesian, clustering
Record Number:CaltechAUTHORS:20160902-093433840
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20160902-093433840
Official Citation:M. Dundar and B. L. Ehlmann, "Rare jarosite detection in crism imagery by non-parametric Bayesian clustering," 2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Los Angeles, CA, 2016, pp. 1-5. doi: 10.1109/WHISPERS.2016.8071747.URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8071747&isnumber=8071655
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:70144
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:02 Sep 2016 18:59
Last Modified:27 Nov 2017 19:29

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