Title :
On the construction of joint probabilistic image models
Author :
Zhang, Ya-Qin ; Loew, Murray H. ; Pickholtz, Raymond L.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., George Washington Univ., Washington, DC, USA
Abstract :
A method is proposed for constructing the joint probability model from a specified first-order distribution and correlation structure. The approach is based on an invertible nonlinear transformation. The model´s information-theoretic properties (entropy, rate-distortion bound) are examined. The results can be used to analyze and evaluate the performance of an image data compression system. It is believed that this class of model and its information-theoretic properties may make for more realistic modeling of medical images and hence their more efficient processing
Keywords :
modelling; patient diagnosis; entropy; image processing; information-theoretic properties; invertible nonlinear transformation; joint probabilistic image models; medical images; model construction; rate-distortion bound; specified first-order distribution; Autocorrelation; Biomedical imaging; Computer science; Entropy; Image analysis; Image reconstruction; Mathematical model; Pattern recognition; Rate-distortion; Vector quantization;
Conference_Titel :
Engineering in Medicine and Biology Society, 1989. Images of the Twenty-First Century., Proceedings of the Annual International Conference of the IEEE Engineering in
Conference_Location :
Seattle, WA
DOI :
10.1109/IEMBS.1989.95900
