Estimation of cloud microstructural parameters from satellite imagery: A Markov random field approach | Zendy

Sujit Basu | Zendy; Mahesh Mohan M. R. | Zendy; VijayK Agarwal | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Estimation of cloud microstructural parameters from satellite imagery: A Markov random field approach

Author(s) -

Sujit Basu,

Mahesh Mohan M. R.,

VijayK 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

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research