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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fu-yuan Hu Yan-ning Zhang Guang-peng Zhang Jing Wang |
| Copyright Year | 2004 |
| Description | Author affiliation: Sch. of Comput., Northwestern Polytech. Univ., Xi'an, China (Fu-yuan Hu; Yan-ning Zhang; Guang-peng Zhang; Jing Wang) |
| Abstract | In this paper, an accurate segmentation approach to high-resolution images based on wavelet-domain Gaussian Markov random field (GMRF) tree models is proposed. The novel wavelet decomposition algorithm and multi-scale segmentation of textured image are presented. This method captures the dependencies across the wavelet subbands and die interscale dependencies that are useful for texture analysis. The power of our technique lies in elective extraction of texture information in high-resolution images. Experiments prove the efficiency of the approach in the segmentation of high-resolution images. |
| Starting Page | 721 |
| Ending Page | 724 |
| File Size | 591983 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780384067 |
| DOI | 10.1109/ICOSP.2004.1452764 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-08-31 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Image resolution Energy resolution Image analysis Markov random fields Costs Density functional theory Frequency Spatial resolution Educational institutions |
| Content Type | Text |
| Resource Type | Article |
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