The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Bayesian tree-structured image modeling using wavelet-domain hidden Markov models
Abstract
Wavelet-domain hidden Markov models have proven to be useful tools for statistical signal and image processing. The hidden Markov tree (HMT) model captures the key features of the joint probability density of the wavelet coefficients of real-world data. One potential drawback to the HMT framework is the need for computationally expensive iterative training to fit an HMT model to a given data set (e.g., using the expectation-maximization algorithm). We greatly simplify the HMT model by exploiting the inherent self-similarity of real-world images. The simplified model specifies the HMT parameters with just nine meta-parameters (independent of the size of the image and the number of wavelet scales). We also introduce a Bayesian universal HMT (uHMT) that fixes these nine parameters. The uHMT requires no training of any kind, while extremely simple, we show using a series of image estimation/denoising experiments that these new models retain nearly all of the key image structure modeled by the full HMT. Finally, we propose a fast shift-invariant HMT estimation algorithm that outperforms other wavelet-based estimators in the current literature, both visually and in mean square error.
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Cites
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Image information and visual quality
Sheikh, H. R., & Bovik, A. C. (2006) · IEEE Transactions on Image Processing · doi:10.1109/tip.2005.859378 · Cited by 4,104
An information fidelity criterion for image quality assessment using natural scene statistics
Sheikh, H. R., Bovik, A. C., & de Veciana, G. (2005) · IEEE Transactions on Image Processing · doi:10.1109/tip.2005.859389 · Cited by 1,399
Model-Based Compressive Sensing
Baraniuk, R. G., Cevher, V., Duarte, M. F., & Hegde, C. (2010) · IEEE Transactions on Information Theory · doi:10.1109/tit.2010.2040894 · Cited by 1,308
Self-citationNo-reference quality assessment using natural scene statistics: JPEG2000
Sheikh, H. R., Bovik, A. C., & Cormack, L. (2005) · IEEE Transactions on Image Processing · doi:10.1109/tip.2005.854492 · Cited by 575
Bayesian Methods for Hidden Markov Models: Recursive Computing in the 21st Century
Scott, S. L. (2002) · Journal of the American Statistical Association · doi:10.1198/016214502753479464 · Cited by 517
Metadata
- Authors
- Romberg, J. K., Choi, H., & Baraniuk, R. G.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2001-07
- Volume
- 10
- Issue
- 7
- Pages
- 1056-1068
- ISSN
- 1057-7149 (ISSN-L)
- OpenAlex
- W2168796889
- Cited by
- 503
- References
- 27
- FWCI
- 27.96
- Type
- journal article
- Language
- en
- Open access
- closed
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