Title: An adaptive segmentation method using MRF model for suburban aerial images

Authors: Mansuo Zhao, David Tien

Addresses: School of Accounting and Computer Science, Charles Sturt University, Bathurst, NSW, Australia. ' School of Accounting and Computer Science, Charles Sturt University, Bathurst, NSW, Australia

Abstract: An adaptive image segmentation method using Markov random field model for suburban aerial images is presented in this paper. The image is modelled as a collection of regions characterised by slowly moving averages and standard deviation. Decreasing sized windows are used to calculate the moving averages during the iteration process. A function based weighting parameter between the two components in the energy function is also used to improve the performance of unsupervised segmentation. A hierarchical implementation scheme is also introduced to reduce the computation load and increase the segmentation speed.

Keywords: aerial suburban images; hierarchical implementation; Markov random field model; adaptive image segmentation.

DOI: 10.1504/IJCAT.2009.024073

International Journal of Computer Applications in Technology, 2009 Vol.34 No.4, pp.235 - 240

Published online: 25 Mar 2009 *

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