Share Email Print
cover

Proceedings Paper

Optimal morphological peak classification
Author(s): Edward R. Dougherty; Yidong Chen
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

The morphological top-hat transform is often used to locate bright peaks in a gray-scale image. The method can be problematic when there are two classes of peaks, one corresponding to valid objects and the other to noise. The present paper employs Bayesian estimation in conjunction with a multinomial distribution corresponding to levels of peak heights in the top-hat image to arrive at an optimal conditional-expectation estimator for the number of images in a random sample of images that contain a given number of valid peaks.

Paper Details

Date Published: 11 August 1995
PDF: 4 pages
Proc. SPIE 2568, Neural, Morphological, and Stochastic Methods in Image and Signal Processing, (11 August 1995); doi: 10.1117/12.216345
Show Author Affiliations
Edward R. Dougherty, Rochester Institute of Technology (United States)
Yidong Chen, Rochester Institute of Technology (United States)


Published in SPIE Proceedings Vol. 2568:
Neural, Morphological, and Stochastic Methods in Image and Signal Processing
Edward R. Dougherty; Francoise J. Preteux; Sylvia S. Shen, Editor(s)

© SPIE. Terms of Use
Back to Top