Color Palette Images Re-indexing by Self Organizing Motor Maps

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dc.contributor.authorBattiato, S.en_US
dc.contributor.authorRundo, F.en_US
dc.contributor.authorStanco, F.en_US
dc.contributor.editorS. Battiato and G. Gallo and F. Stancoen_US
dc.date.accessioned2014-01-27T16:20:48Z
dc.date.available2014-01-27T16:20:48Z
dc.date.issued2006en_US
dc.description.abstractPalette re-ordering is a well known and very effective approach for improving the compression of color-indexed images. If the spatial distribution of the indexes in the image is smooth, greater compression ratios may be obtained. As known, obtaining an optimal re-indexing scheme is not a simple problem. In this paper we provide a novel algorithm for palette re-ordering problem showing the advantages of using a neural network instead of classical heuristic methods. We propose to apply the Motor Map neural network which is considered an extension of the well-known SOM Kohonen neural network. Experiments confirm the effectiveness of the proposed technique.en_US
dc.description.seriesinformation4th Eurographics Italian Chapter Conferenceen_US
dc.identifier.isbn3-905673-58-4en_US
dc.identifier.urihttps://doi.org/10.2312/LocalChapterEvents/ItalianChapConf2006/241-246en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.4.2 [Image processing and Computer Vision]: Compression (Coding)en_US
dc.titleColor Palette Images Re-indexing by Self Organizing Motor Mapsen_US
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