Imaging applications of stochastic minimal graphs

Author

Hero, Alfred ; Bing Ma ; Michel, Olivier

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI

Volume

3

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

573

Abstract

This paper presents an overview of some of the theory and application of stochastic minimal graphs in the context of entropy estimation for imaging applications. Stochastic graphs which span a set of extracted image features can be constructed to yield consistent estimators of Jensen´s entropy difference for between pairs of images. Unlike traditional plug-in entropy estimates based on density estimation, stochastic graph methods provide direct estimates of these quantities. We review the stochastic graph approach to entropy estimation, compare convergence rates to that of plug-in estimators, and discuss a geo-registration application

Keywords

cartography; convergence of numerical methods; entropy; graph theory; image registration; parameter estimation; stochastic processes; Jensen´s entropy difference; convergence rates; density estimation; digital elevation model; entropy estimation; geo-registration application; image features extraction; imaging applications; plug-in entropy estimates; stochastic minimal graphs; Circuit testing; Image coding; Image processing; Image storage; Mobile communication; Packaging; Standardization; Telephony; Video coding; Video compression;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2001. Proceedings. 2001 International Conference on

Conference_Location

Thessaloniki

Print_ISBN

0-7803-6725-1

Type

conf

DOI

10.1109/ICIP.2001.958181

Filename

958181