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.
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Published: Animo Repository 2013
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/9323
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-96412023-05-16T01:46:19Z 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/9323 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/9323
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