An image model based on occluding object images and maximum entropy

This paper introduces a statistical image model based on occlusion and maximum entropy. The statistical model combines a fundamental property of image formation, occlusion, with both object-image shape and nonuniform object-image intensity. The model is a composition of individual object-images that...

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Bibliographic Details
Published in:IEEE transactions on image processing 1998-09, Vol.7 (9), p.1300-1310
Main Authors: Stuller, J.A., Shah, R.
Format: Article
Language:English
Subjects:
Applied sciences
Autocorrelation
Entropy
Exact sciences and technology
Image coding
Image edge detection
Image processing
Information, signal and communications theory
Mathematical model
Probability density function
Shape
Signal processing
Statistics
Telecommunications and information theory
Two dimensional displays
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Summary:This paper introduces a statistical image model based on occlusion and maximum entropy. The statistical model combines a fundamental property of image formation, occlusion, with both object-image shape and nonuniform object-image intensity. The model is a composition of individual object-images that have random positions, shapes, and intensities, and that occlude both background and one another. We derive the autocorrelation and second-order probability density functions of this model and give several examples.
ISSN:1057-7149
1941-0042
DOI:10.1109/83.709662