Polarimetric SAR image segmentation with hidden Markov random field models

Author

Harger, Robert O.

Author_Institution

Dept. of Electr. Eng., Maryland Univ., College Park, MD, USA

fYear

1991

fDate

7-10 Apr 1991

Firstpage

611

Abstract

A segmentation algorithm based on a hidden Markov random field model is applied to a (HH, VV) polarimetric SAR (synthetic aperture radar) image pair. The segmentations, assuming two classes, of the HH and VV images separately are shown, after 100 stages of stochastic relaxation. The results agree with the visual perception of the images. The segmentation, assuming two classes, of HH and VV images jointly is also shown, again after 100 stages

Keywords

Markov processes; electromagnetic wave polarisation; picture processing; radar; HH images; VV images; hidden Markov random field models; image segmentation algorithm; polarimetric SAR; stochastic relaxation; synthetic aperture radar; visual perception; Annealing; Convergence; Distributed computing; Hidden Markov models; Image processing; Image segmentation; Maximum likelihood estimation; Parameter estimation; Roads; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Southeastcon '91., IEEE Proceedings of

Conference_Location

Williamsburg, VA

Print_ISBN

0-7803-0033-5

Type

conf

DOI

10.1109/SECON.1991.147828

Filename

147828

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3554038