16 December 1992 Learning structural and corruption information from samples for Markov-random-field edge detection enhancement
Author Affiliations +
Proceedings Volume 1766, Neural and Stochastic Methods in Image and Signal Processing; (1992); doi: 10.1117/12.130826
Event: San Diego '92, 1992, San Diego, CA, United States
Abstract
We have advanced Markov random field research by addressing the issue of obtaining a reasonable, non-trivial, noise model. We have introduced the concept of a double neighborhood MRF. In the past we have estimated MRF probabilities by sampling neighborhood frequencies from images. Now we address the issue of noise models by sampling from pairs of original images together with noisy imagery. Thus we create a probability density function for pairs of neighborhoods across both images. This models the noise within the MRF probability density function without having to make assumptions about its form. This provides an easy way to generate Markov random fields for annealing or other relaxation methods. We have successfully applied this technique, combined with a technique of Hancock and Kittler which adds theoretical noise to an MRF density function, to the problem binary image reconstruction. We now apply it to edge detection enhancement of artificial images. We train the double neighborhood MRF on true edge-maps and edge-maps generated as output of a Sobel edge detector. Our method improves the generated edge-maps - - visually, and using the metrics of number of bits incorrect, and Pratt's figure of merit for edge detectors. We have also successfully improved the output edge-maps of some real images.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Davin Milun, David B. Sher, "Learning structural and corruption information from samples for Markov-random-field edge detection enhancement", Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); doi: 10.1117/12.130826; https://doi.org/10.1117/12.130826
PROCEEDINGS
10 PAGES


SHARE
KEYWORDS
Smoothing

Magnetorheological finishing

Edge detection

Sensors

Detection and tracking algorithms

Signal processing

Stochastic processes

RELATED CONTENT

Optimal algorithm for detecting two-dimensional images
Proceedings of SPIE (February 27 1996)
Use of directional consistency with Sobel edge detector
Proceedings of SPIE (September 01 1990)
Edge detection of remote sensing image based on Wold like...
Proceedings of SPIE (October 28 2006)
New approach to the analysis of IR images
Proceedings of SPIE (September 01 1995)

Back to Top