Modeling and estimation for a class of multiresolution random fields

Modeling and estimation for a class of multiresolution random fields

Discusses a class of multiresolution models of random fields based on a generalization of the midpoint deflection construction of the 1D Brownian motion. The authors then present least squares (LS) algorithms for the estimation of parameters which define these models and hence provide a framework fo...

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Bibliographische Detailangaben
Hauptverfasser: Milanfar, P., Tenney, R.R., Washburn, R.B., Willsky, A.S.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Fractals
Image analysis
Interpolation
Least squares approximation
Nonlinear equations
Object detection
Parameter estimation
Recursive estimation
System identification
Yield estimation
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Beschreibung
Zusammenfassung:Discusses a class of multiresolution models of random fields based on a generalization of the midpoint deflection construction of the 1D Brownian motion. The authors then present least squares (LS) algorithms for the estimation of parameters which define these models and hence provide a framework for synthesizing and analyzing images with fractal-like properties such as those found in statistical representation of natural terrain and other geophysical phenomena. The authors also briefly discuss possible applications of this modeling framework to target detection in images.< >
DOI:10.1109/ICIP.1994.413819