A COMBINED MARKOV RANDOM-FIELD AND WAVE-PACKET TRANSFORM-BASED APPROACH FOR IMAGE SEGMENTATION

被引:22
作者
BELLO, MG
机构
[1] The Charles Stark Draper Laboratory, Cambridge
关键词
D O I
10.1109/83.336251
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The present work formulates a novel segmentation algorithm which combines the use of Markov random field models for image-modeling with the use of the discrete wave-packet transform for image analysis. Image segmentations are derived and refined at a sequence of resolution levels, using as data selected wave-packet transform images or ''channels.'' The described segmentation algorithm is compared with non-multiresolution Markov random field-based image segmentation algorithms in the contest of synthetic image example problems, and found to be both significantly more efficient and effective.
引用
收藏
页码:834 / 846
页数:13
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