Title :
A stochastic one-dimensional image model based on occluding object images
Author :
Stuller, John A.
Author_Institution :
Dept. of Electr. Eng., Missouri Univ., Rolla, MO, USA
fDate :
31 Oct-2 Nov 1994
Abstract :
This paper provides new insights into the formation of one-dimensional (line-scan) image autocorrelation functions. We model a line scan as a composition of individual object-images that have random positions, widths and intensities and that occlude one another. We derive the autocorrelation function of this model as a function of object-image width and intensity distributions. We show that any assumption regarding the form of the autocorrelation function places a constraint on object-image width and intensity distributions and we derive the object-image width distribution associated with the widely used symmetric-exponential autocovariance model
Keywords :
correlation methods; image processing; stochastic processes; image autocorrelation functions; intensity distributions; line-scan; object-image width; occluding object images; random positions; stochastic one-dimensional image model; symmetric-exponential autocovariance model; Autocorrelation; Layout; Random processes; Stochastic processes;
Conference_Titel :
Signals, Systems and Computers, 1994. 1994 Conference Record of the Twenty-Eighth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-6405-3
DOI :
10.1109/ACSSC.1994.471409
