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Titolo:
INFORMATIVE PRIORS FOR THE BAYESIAN CLASSIFICATION OF SATELLITE IMAGES
Autore:
FRIGESSI A; STANDER J;
Indirizzi:
UNIV VENICE,STAT LAB VENICE ITALY CNR,IST APPLICAZ CALCOLO ROME ITALY
Titolo Testata:
Journal of the American Statistical Association
fascicolo: 426, volume: 89, anno: 1994,
pagine: 703 - 709
Fonte:
ISI
Lingua:
ENG
Keywords:
GEOGRAPHICAL INFORMATION SYSTEM; ICM ALGORITHM; IMAGE RECONSTRUCTION; MARKOV RANDOM FIELDS; QUALITY ASSESSMENT; REMOTE SENSING;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
CompuMath Citation Index
Science Citation Index Expanded
Citazioni:
8
Recensione:
Indirizzi per estratti:
Citazione:
A. Frigessi e J. Stander, "INFORMATIVE PRIORS FOR THE BAYESIAN CLASSIFICATION OF SATELLITE IMAGES", Journal of the American Statistical Association, 89(426), 1994, pp. 703-709

Abstract

In the Bayesian classification of satellite images, a prior distribution is used that aims to model the belief of spatial homogeneity of the underlying region. We extend this prior distribution to model certain topographical features of the area such as the position of the roads, the slopes, and the aspects. We demonstrate the effectiveness of this prior distribution in a reconstruction algorithm by means of a simulation study in which the quality of the result is assessed by a comparison of estimated and known covertypes. We apply the algorithm to realdata with success.

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Documento generato il 24/09/20 alle ore 05:20:49