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| Content Provider | IEEE Xplore Digital Library | 
|---|---|
| Author | Fang Liu Picard, R.W. | 
| Copyright Year | 1999 | 
| Description | Author affiliation: Lincoln Lab., MIT, Lexington, MA, USA (Fang Liu) | 
| Abstract | The theory of the 2-D Wold decomposition of homogeneous random fields is effective in image and video analysis, synthesis, and modeling. However, a robust and computationally efficient decomposition algorithm is needed for use of the theory in practical applications. This paper presents a spectral 3-D Wold decomposition algorithm for homogeneous and near homogeneous random fields. The algorithm relies on the intrinsic fundamental-harmonic relationship among Fourier spectral peaks to identify harmonic frequencies, and uses a Hough transformation to detect spectral evanescent components. A local variance based procedure is developed to determine the spectral peak support. Compared to the two other existing methods for Wold decompositions, global thresholding and maximum-likelihood parameter estimation, this algorithm is more robust and flexible for the large variety of natural images, as well as computationally more efficient than the maximum-likelihood method. | 
| Starting Page | 3501 | 
| Ending Page | 3504 | 
| File Size | 472811 | 
| Page Count | 4 | 
| File Format | |
| ISBN | 0780350413 | 
| ISSN | 15206149 | 
| DOI | 10.1109/ICASSP.1999.757597 | 
| Language | English | 
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Publisher Date | 1999-03-15 | 
| Publisher Place | USA | 
| Access Restriction | Subscribed | 
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Subject Keyword | Robustness Laboratories Maximum likelihood estimation Humans Maximum likelihood detection Image segmentation Image analysis Image coding Pattern matching Character recognition | 
| Content Type | Text | 
| Resource Type | Article | 
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