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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ghouti, L. Bouridane, A. Ibrahim, M.K. |
| Copyright Year | 2005 |
| Description | Author affiliation: Sch. of Comput. Sci., Queen's Univ., Belfast, UK (Ghouti, L.; Bouridane, A.) |
| Abstract | We consider the problem of improving the performance of multiwavelets-based image coders through texture parametrization. Texture parametrization is designed to achieve higher compression rates while maintaining excellent visual image quality. Tradeoffs among these two conflicting goals, maximizing compression rate and minimizing distortion due to compression, are possible by taking into account the imperfections inherent in the human visual system (HVS). We present a statistical view of the texture parametrization using balanced multiwavelets and develop a hybrid image compression scheme. The statistical scheme leads to a new multiresolution-based texture parametrization relying on the accurate modeling of the marginal distribution of balanced multiwavelet coefficients using generalized Gaussian density (GGD). Furthermore, we show that the proposed texture parametrization scheme is computationally-efficient. The proposed hybrid codec can be seamlessly integrated in any embedded image coder while requiring minimal header data. |
| Starting Page | 2313 |
| Ending Page | 2316 |
| File Size | 621388 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780388348 |
| DOI | 10.1109/ISCAS.2005.1465087 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-05-23 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image coding Stochastic processes Power system modeling Humans Visual system Image storage Computer science Decoding Filter bank Image quality |
| Content Type | Text |
| Resource Type | Article |
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