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A Relaxation Method for Multispectral Pixel Classification
January 1980 (vol. 2 no. 1)
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.
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 and Machine Intelligence, vol. 2, no. 1, pp. 72-75, Jan. 1980, doi:10.1109/TPAMI.1980.4766973
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