Fast search for best representations in multitree dictionaries
We address the best basis problem--or, more generally, the best representation problem: Given a signal, a dictionary of representations, and an additive cost function, the aim is to select the representation from the dictionary which minimizes the cost for the given signal. We develop a new framewor...
| Publié dans: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1997. - 15(2006), 7 vom: 30. Juli, Seite 1779-93 |
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| Auteur principal: | |
| Autres auteurs: | , , |
| Format: | Article |
| Langue: | English |
| Publié: |
2006
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| Accès à la collection: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Sujets: | Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. |
| Résumé: | We address the best basis problem--or, more generally, the best representation problem: Given a signal, a dictionary of representations, and an additive cost function, the aim is to select the representation from the dictionary which minimizes the cost for the given signal. We develop a new framework of multitree dictionaries, which includes some previously proposed dictionaries as special cases. We show how to efficiently find the best representation in a multitree dictionary using a recursive tree-pruning algorithm. We illustrate our framework through several examples, including a novel block image coder, which significantly outperforms both the standard JPEG and quadtree-based methods and is comparable to embedded coders such as JPEG2000 and SPIHT |
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| Description: | Date Completed 08.08.2006 Date Revised 26.10.2019 published: Print Citation Status MEDLINE |
| ISSN: | 1057-7149 |