Title :
An image model based on occluding object images and maximum entropy
Author :
Stuller, John A. ; Shah, Rahul
Author_Institution :
Dept. of Electr. & Comput. Eng., Missouri Univ., Rolla, MO, USA
fDate :
9/1/1998 12:00:00 AM
Abstract :
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
Keywords :
correlation methods; image processing; maximum entropy methods; probability; random processes; statistical analysis; autocorrelation; background; image formation; maximum entropy; nonuniform object-image intensity; object images; object-image shape; occlusion; random intensities; random positions; random shapes; second-order probability density functions; statistical image model; Autocorrelation; Entropy; Image coding; Image edge detection; Image processing; Mathematical model; Probability density function; Shape; Statistics; Two dimensional displays;
Journal_Title :
Image Processing, IEEE Transactions on
