@InProceedings{FreryFerrBust:2006:AcStCl,
author = "Frery, Alejandro C{\'e}sar and Ferrero, Susana and Bustos, Oscar
Humberto",
affiliation = "{Universidade Federal de Alagoas} and {Universidad Nacional de
R{\'{\i}}o Cuarto} and {Universidad Nacional de C{\'o}rdoba}",
title = "Accuracy of Statistical Classification Strategies in Remote
Sensing Imagery",
booktitle = "Proceedings...",
year = "2006",
editor = "Oliveira Neto, Manuel Menezes de and Carceroni, Rodrigo Lima",
organization = "Brazilian Symposium on Computer Graphics and Image Processing, 19.
(SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "image classification, accuracy, contextual classification.",
abstract = "We present the assessment of two classification procedures using a
Monte Carlo experience and Landsat data. Classification
performance is hard to assess with generality due to the huge
number of variables involved. In this case we consider the problem
of classifying multispectral optical imagery with pointwise
Gaussian Maximum Likelihood and contextual ICM (Iterated
Conditional Modes), with and without errors in the training stage.
Using simulation the ground truth is known and, therefore, precise
comparisons are possible. The contextual approach proved being
superior than the pointwise one, at the expense of requiring more
computational resources, with both real and simulated data.
Quantitative and qualitative results are discussed.",
conference-location = "Manaus, AM, Brazil",
conference-year = "8-11 Oct. 2006",
doi = "10.1109/SIBGRAPI.2006.4",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2006.4",
language = "en",
ibi = "6qtX3pFwXQZG2LgkFdY/LN2Bx",
url = "http://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/LN2Bx",
targetfile = "frery-AccuracyClassification.pdf",
urlaccessdate = "2025, Feb. 10"
}