Open AccessEstimation of cloud microstructural parameters from satellite imagery: A Markov random field approach
Author(s) -
Samik Basu,
M R Mahesh Mohan,
Vijay K. Agarwal
Publication year - 1989
Publication title -
mausam
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.243
H-Index - 12
ISSN - 0252-9416
DOI - 10.54302/mausam.v40i3.2108
Subject(s) - cloud computing , markov random field , satellite , markov chain , computer science , satellite imagery , field (mathematics) , remote sensing , cluster analysis , markov chain monte carlo , estimation , monte carlo method , maximum likelihood , markov process , meteorology , markov model , statistics , image (mathematics) , artificial intelligence , geology , mathematics , geography , image segmentation , machine learning , engineering , aerospace engineering , systems engineering , pure mathematics , operating system
Estimation of microstructural parameters controlling clustering in different directions or a cloud scene is investigated. The cloud scene is represent.ed as a Markov ran~om field and the parameters are estimated by a maximum likelihood technique. A surrogate Image, corresp°!ldmg to each scene, is generated by a Monte-Carlo procedure. Results of analysing NOAA and INSA T cloud Images are presented