Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10359505 | Image and Vision Computing | 2005 | 9 Pages |
Abstract
We propose a method based on the Hidden Markov Tree (HMT) model for multiscale image segmentation in the wavelet domain. We use the inherent tree structure of the model to segment the image at a range of different scales. We then merge these different scale segmented images using boundary refinement conditions. The final segmented image utilizes the reliability of coarse scale segmented images and the fineness of finer scales segmented images. We demonstrate the performance of the algorithm on synthetic data and aerial photos.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Etai Mor, Mayer Aladjem,