Fractal modeling and analysis of Poisson processes

Author

Nowak, Robert D.

Author_Institution

Dept. of ECE, Michigan State Univ., East Lansing, MI, USA

Volume

1

fYear

1998

fDate

1-4 Nov. 1998

Firstpage

727

Abstract

This paper describes a new fractal modeling and analysis approach for a point processes based on a previously proposed multiscale model for Poisson processes. A new Bayesian hypothesis testing framework is proposed for detecting or classifying fractal characteristics of an intensity based on observations of the associated point process. The test statistics can be expressed in closed-form, and asymptotic analysis reveals a simple mechanism at work. Applications to photon-limited image edge detection are discussed.

Keywords

Bayes methods; Poisson distribution; edge detection; fractals; signal classification; Bayesian hypothesis testing; Poisson processes; asymptotic analysis; closed-form expression; fractal analysis; fractal characteristics classification; fractal characteristics detection; fractal modeling; multiscale model; multiscale multiplicative innovations model; photon-limited image edge detection; point processes; test statistics; Bayesian methods; Binary trees; Fractals; Image edge detection; Information analysis; Probability; Statistical analysis; Technological innovation; Testing; Wavelet coefficients;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems & Computers, 1998. Conference Record of the Thirty-Second Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-7803-5148-7

Type

conf

DOI

10.1109/ACSSC.1998.750957

Filename

750957