A scale-recursive, statistically-based method for anomaly characterization in images based upon observations of scattered radiation

Author

Miller, Eric L.

Author_Institution

Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA

Volume

1

fYear

1995

fDate

23-26 Oct 1995

Firstpage

490

Abstract

A scale-recursive algorithm is presented for the detection and characterization of anomalous structures in a medium based upon observations of scattered radiation obtained along the boundary of the region. A nonlinear scattering model based upon Maxwell´s equation is used to relate the anomalous structures to the measured fields. Decision- and estimation-theoretic techniques are employed to (a) identify large-scale areas in which such anomalies are present and (b) spatially refine these estimated regions to better localize the true anomalous structures. Examples are presented from a low-frequency inverse conductivity problem drawn from the field of geophysical signal processing

Keywords

Maxwell equations; decision theory; electromagnetic wave scattering; geophysical prospecting; geophysical signal processing; image processing; inverse problems; recursive estimation; statistical analysis; terrestrial electricity; Maxwell´s equation; anomaly characterization; decision-theoretic techniques; estimation-theoretic techniques; geophysical signal processing; images; low-frequency inverse conductivity problem; measured fields; nonlinear scattering model; scale-recursive algorithm; scattered radiation; statistically-based method; Buildings; Conductivity; Geophysical measurements; Geophysics computing; Large-scale systems; Maxwell equations; Nonlinear equations; Radiation detectors; Scattering; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1995. Proceedings., International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-8186-7310-9

Type

conf

DOI

10.1109/ICIP.1995.529753

Filename

529753