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Issue No.01 - January (1980 vol.2)
pp: 72-75
J. O. Eklundh , Defense Research Institute, Stockholm, Sweden.
H. Yamamoto , National Aerospace Laboratory, Tokyo, Japan.
A. Rosenfeld , Computer Science Center, University of Maryland, College Park, MD 20742.
ABSTRACT
Three approaches to reducing errors in multispectral pixel classification were compared: 1) postprocessing (iterated reclassification based on comparison with the neighbors' classes); 2) preprocessing (iterated smoothing, by averaging with selected neighbors, prior to classification); and 3) relaxation (probabilistic classification followed by iterative probability adjustment). In experiments using a color image of a house, the relaxation approach gave markedly superior performance; relaxation eliminated 4-8 times as many errors as the other methods did.
CITATION
J. O. Eklundh, H. Yamamoto, A. Rosenfeld, "A Relaxation Method for Multispectral Pixel Classification", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.2, no. 1, pp. 72-75, January 1980, doi:10.1109/TPAMI.1980.4766973
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