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PIMS--Multispectral Image Processing Tool for Semantic Information Detection Based on Vegetation Indices
Timisoara, Romania September 26-September 29
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SYNASC.2006.60Eighth International Symposium on Sym ...
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Cornelia Melenti, Daniel Safta, Dorian Gorgan, "PIMS--Multispectral Image Processing Tool for Semantic Information Detection Based on Vegetation Indices," Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on, pp. 279-288, Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'06), 2006.
 
 
BibTex
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@article{ 10.1109/SYNASC.2006.60,
author = {Cornelia Melenti and Daniel Safta and Dorian Gorgan},
title = {PIMS--Multispectral Image Processing Tool for Semantic Information Detection Based on Vegetation Indices},
journal ={Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on},
volume = {0},
year = {2006},
isbn = {0-7695-2740-X},
pages = {279-288},
doi = {http://doi.ieeecomputersociety.org/10.1109/SYNASC.2006.60},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on
TI - PIMS--Multispectral Image Processing Tool for Semantic Information Detection Based on Vegetation Indices
SN - 0-7695-2740-X
SP279
EP288
A1 - Cornelia Melenti,
A1 - Daniel Safta,
A1 - Dorian Gorgan,
PY - 2006
KW - null
VL - 0
JA - Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on
ER -
 
Cornelia Melenti, Technical University of Cluj-Napoca, Romania
Daniel Safta, Technical University of Cluj-Napoca, Romania
Dorian Gorgan, Technical University of Cluj-Napoca, Romania
This paper approaches the opportunity of the use of medium and high spatial resolution satellite images for the study of the extent and structure of the vegetation cover for a certain geographic area.

A computerized system for the classification of vegetation was created based on vegetation indices determined from various combinations of spectral bands from high resolution multispectral satellite images. The comparative study and analysis of vegetation indices in a given image, the acquirement of statistical data and their export to a database are reported.

Citation:
Cornelia Melenti, Daniel Safta, Dorian Gorgan, "PIMS--Multispectral Image Processing Tool for Semantic Information Detection Based on Vegetation Indices," synasc, pp.279-288, Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'06), 2006
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