Feature extraction from digitized images of dye solutions as a model for algal bloom remote sensing

Digital images of dye solutions were obtained under controlled conditions to simulate images of algal blooms. The images were dissected and analyzed using RGB color space to determine color feature-pigment concentration correlations. The results indicate that the technique may be used in the determi...

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Main Authors:	Punzalan, Eric R., Ong, Prane Mariel B., Carandang, Jose Santos R., Vi, Santos, Gil Nonato C., Mulingbayan, Isa Mae C., Sanchez, Azzedine Erika C., Go, Natasha Pauline A., Huang, Jialing L.
Format:	text
Published:	Animo Repository 2013
Subjects:	Algal blooms—Remote sensing Digital image correlation Chemistry Physics
Online Access:	https://animorepository.dlsu.edu.ph/faculty_research/9324
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Institution:	De La Salle University

id	oai:animorepository.dlsu.edu.ph:faculty_research-11222
record_format	eprints
spelling	oai:animorepository.dlsu.edu.ph:faculty_research-112222023-05-16T01:46:13Z Feature extraction from digitized images of dye solutions as a model for algal bloom remote sensing Punzalan, Eric R. Ong, Prane Mariel B. Carandang, Jose Santos R., Vi Santos, Gil Nonato C. Mulingbayan, Isa Mae C. Sanchez, Azzedine Erika C. Go, Natasha Pauline A. Huang, Jialing L. Digital images of dye solutions were obtained under controlled conditions to simulate images of algal blooms. The images were dissected and analyzed using RGB color space to determine color feature-pigment concentration correlations. The results indicate that the technique may be used in the determination of algal bloom levels / water pigmentation by application of the same analysis to aerial photos of HAB affected bodies of water. 2013-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/9324 Faculty Research Work Animo Repository Algal blooms—Remote sensing Digital image correlation Chemistry Physics
institution	De La Salle University
building	De La Salle University Library
continent	Asia
country	Philippines Philippines
content_provider	De La Salle University Library
collection	DLSU Institutional Repository
topic	Algal blooms—Remote sensing Digital image correlation Chemistry Physics
spellingShingle	Algal blooms—Remote sensing Digital image correlation Chemistry Physics Punzalan, Eric R. Ong, Prane Mariel B. Carandang, Jose Santos R., Vi Santos, Gil Nonato C. Mulingbayan, Isa Mae C. Sanchez, Azzedine Erika C. Go, Natasha Pauline A. Huang, Jialing L. Feature extraction from digitized images of dye solutions as a model for algal bloom remote sensing
description	Digital images of dye solutions were obtained under controlled conditions to simulate images of algal blooms. The images were dissected and analyzed using RGB color space to determine color feature-pigment concentration correlations. The results indicate that the technique may be used in the determination of algal bloom levels / water pigmentation by application of the same analysis to aerial photos of HAB affected bodies of water.
format	text
author	Punzalan, Eric R. Ong, Prane Mariel B. Carandang, Jose Santos R., Vi Santos, Gil Nonato C. Mulingbayan, Isa Mae C. Sanchez, Azzedine Erika C. Go, Natasha Pauline A. Huang, Jialing L.
author_facet	Punzalan, Eric R. Ong, Prane Mariel B. Carandang, Jose Santos R., Vi Santos, Gil Nonato C. Mulingbayan, Isa Mae C. Sanchez, Azzedine Erika C. Go, Natasha Pauline A. Huang, Jialing L.
author_sort	Punzalan, Eric R.
title	Feature extraction from digitized images of dye solutions as a model for algal bloom remote sensing
title_short	Feature extraction from digitized images of dye solutions as a model for algal bloom remote sensing
title_full	Feature extraction from digitized images of dye solutions as a model for algal bloom remote sensing
title_fullStr	Feature extraction from digitized images of dye solutions as a model for algal bloom remote sensing
title_full_unstemmed	Feature extraction from digitized images of dye solutions as a model for algal bloom remote sensing
title_sort	feature extraction from digitized images of dye solutions as a model for algal bloom remote sensing
publisher	Animo Repository
publishDate	2013
url	https://animorepository.dlsu.edu.ph/faculty_research/9324
_version_	1767197033223946240

Feature extraction from digitized images of dye solutions as a model for algal bloom remote sensing

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