Stochastic image models generated by random tessellations of the plane

J. W. Modestino; R. W. Fries; A. L. Vickers

doi:10.1016/0146-664X(80)90005-2

Stochastic image models generated by random tessellations of the plane

J. W. Modestino, R. W. Fries, A. L. Vickers

Electrical & Computer Engineering

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

A useful class of two-dimensional (2-D) random fields is described which can be generated by random tessellations of the plane. The random tessellations are in turn generated by marked point processes evolving according to a spatial parameter. Gray levels are assigned within elementary disjoint regions generated by the tessellations to have specified correlation properties with gray levels in contiguous regions. A complete second-order statistical description of the resulting class of random fields is provided. This includes not only autocorrelation functions and power spectral densities but joint probability density functions. Several applications are discussed including the modeling of real-world imagery possessing inherent edge structure.

Original language	English (US)
Pages (from-to)	74-98
Number of pages	25
Journal	Computer Graphics and Image Processing
Volume	12
Issue number	1
DOIs	https://doi.org/10.1016/0146-664X(80)90005-2
State	Published - Jan 1980

ASJC Scopus subject areas

Environmental Science(all)
Earth and Planetary Sciences(all)

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10.1016/0146-664X(80)90005-2

Cite this

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title = "Stochastic image models generated by random tessellations of the plane",

abstract = "A useful class of two-dimensional (2-D) random fields is described which can be generated by random tessellations of the plane. The random tessellations are in turn generated by marked point processes evolving according to a spatial parameter. Gray levels are assigned within elementary disjoint regions generated by the tessellations to have specified correlation properties with gray levels in contiguous regions. A complete second-order statistical description of the resulting class of random fields is provided. This includes not only autocorrelation functions and power spectral densities but joint probability density functions. Several applications are discussed including the modeling of real-world imagery possessing inherent edge structure.",

author = "Modestino, {J. W.} and Fries, {R. W.} and Vickers, {A. L.}",

note = "Funding Information: In this paper a useful class of 2-D random fields appropriate for this purpose are described and several of their more important properties discussed. This * This work was supported in part by ONR under Contract N00014-75-C-0281 and in part by USAF RADC under Contract AF30602-78-C-0083. ? R. W. Fries is now with Pattern Analysis and Recognition Corp., Rome, N.Y.",

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AU - Vickers, A. L.

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N2 - A useful class of two-dimensional (2-D) random fields is described which can be generated by random tessellations of the plane. The random tessellations are in turn generated by marked point processes evolving according to a spatial parameter. Gray levels are assigned within elementary disjoint regions generated by the tessellations to have specified correlation properties with gray levels in contiguous regions. A complete second-order statistical description of the resulting class of random fields is provided. This includes not only autocorrelation functions and power spectral densities but joint probability density functions. Several applications are discussed including the modeling of real-world imagery possessing inherent edge structure.

AB - A useful class of two-dimensional (2-D) random fields is described which can be generated by random tessellations of the plane. The random tessellations are in turn generated by marked point processes evolving according to a spatial parameter. Gray levels are assigned within elementary disjoint regions generated by the tessellations to have specified correlation properties with gray levels in contiguous regions. A complete second-order statistical description of the resulting class of random fields is provided. This includes not only autocorrelation functions and power spectral densities but joint probability density functions. Several applications are discussed including the modeling of real-world imagery possessing inherent edge structure.

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Stochastic image models generated by random tessellations of the plane

Abstract

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