Unsupervised image segmentation combining region and boundary estimation
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摘要
An integrated approach to image segmentation is presented that combines region and boundary information using maximum a posteriori estimation and decision theory. The algorithm employs iterative, decision-directed estimation performed on a novel multi-resolution representation. The use of a multi-resolution technique ensures both robustness in noise and efficiency of computation, while the model-based estimation and decision process is flexible and spatially local, thus avoiding assumptions about global homogeneity or size and number of regions. A comparative evaluation of the method against region-only and boundary-only methods is presented and is shown to produce accurate segmentations at quite low signal-to-noise ratios.
论文关键词:Image segmentation,Multiresolution,MAP estimation
论文评审过程:Received 7 October 1999, Revised 11 August 2000, Accepted 4 September 2000, Available online 27 April 2001.
论文官网地址:https://doi.org/10.1016/S0262-8856(00)00084-6