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ICIP
2002
IEEE
14 years 7 months ago
Unsupervised image segmentation via Markov trees and complex wavelets
The goal in image segmentation is to label pixels in an image based on the properties of each pixel and its surrounding region. Recently Content-Based Image Retrieval (CBIR) has e...
Cián W. Shaffrey, Ian Jermyn, Nick G. Kings...
ICMCS
2009
IEEE
415views Multimedia» more  ICMCS 2009»
13 years 3 months ago
A new localized superpixel Markov random field for image segmentation
In this paper, we present a novel localized Markov random field (MRF) method based on superpixels for region segmentation. Early vision problems could be formulated as pixel label...
Xiaofeng Wang, Xiao-Ping Zhang
SSIAI
2000
IEEE
13 years 10 months ago
Pairwise Markov Random Fields and its Application in Textured Images Segmentation
The use of random fields, which allows one to take into account the spatial interaction among random variables in complex systems, is a frequent tool in numerous problems of stati...
Wojciech Pieczynski, Abdel-Nasser Tebbache
ICPR
2006
IEEE
14 years 6 months ago
Unsupervised Segmentation Using Gabor Wavelets and Statistical Features in LIDAR Data Analysis
In this paper, we address issues in segmentation of remotely sensed LIDAR (LIght Detection And Ranging) data. The LIDAR data, which were captured by airborne laser scanner, contai...
Hong Wei, Marc Bartels
ICPR
2004
IEEE
14 years 6 months ago
Unsupervised Image Segmentation Using A Simple MRF Model with A New Implementation Scheme
A Markov random field (MRF) model with a new implementation scheme is proposed for unsupervised image segmentation based on image features. The traditional two-component MRF model...
David A. Clausi, Huawu Deng