TY - GEN
T1 - IMAGE SEGMENTATION ALGORITHM BASED ON RELAXATION WITH VARYING NEIGHBORHOOD STRUCTURES.
AU - Derin, Haluk
AU - Won, Chee Sun
AU - Kuang, Jinyu
PY - 1987
Y1 - 1987
N2 - A segmentation algorithm based on deterministic relaxation with varying neighborhood structures is presented. The image is modeled as a discrete-valued Markov random field (MRF), or equivalently a Gibbs random field, corrupted by additive, independent, Gaussian noise. The algorithm seeks to determine the maximum a posteriori (MAP) estimate of noiseless scene. A comparison of this segmentation algorithm with other relaxation algorithms and a single-sweep dynamic programming algorithm, all seeking the MAP estimate, is also presented.
AB - A segmentation algorithm based on deterministic relaxation with varying neighborhood structures is presented. The image is modeled as a discrete-valued Markov random field (MRF), or equivalently a Gibbs random field, corrupted by additive, independent, Gaussian noise. The algorithm seeks to determine the maximum a posteriori (MAP) estimate of noiseless scene. A comparison of this segmentation algorithm with other relaxation algorithms and a single-sweep dynamic programming algorithm, all seeking the MAP estimate, is also presented.
UR - http://www.scopus.com/inward/record.url?scp=0023211029&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0023211029
SN - 0818608161
T3 - Conference Record - Asilomar Conference on Circuits, Systems & Computers
SP - 439
EP - 443
BT - Conference Record - Asilomar Conference on Circuits, Systems & Computers
PB - IEEE
ER -