Color Palette Images Re-indexing by Self Organizing Motor Maps
Abstract
Palette 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.
BibTeX
@inproceedings {10.2312:LocalChapterEvents:ItalianChapConf2006:241-246,
booktitle = {4th Eurographics Italian Chapter Conference},
editor = {S. Battiato and G. Gallo and F. Stanco},
title = {{Color Palette Images Re-indexing by Self Organizing Motor Maps}},
author = {Battiato, S. and Rundo, F. and Stanco, F.},
year = {2006},
publisher = {The Eurographics Association},
ISBN = {3-905673-58-4},
DOI = {10.2312/LocalChapterEvents/ItalianChapConf2006/241-246}
}
booktitle = {4th Eurographics Italian Chapter Conference},
editor = {S. Battiato and G. Gallo and F. Stanco},
title = {{Color Palette Images Re-indexing by Self Organizing Motor Maps}},
author = {Battiato, S. and Rundo, F. and Stanco, F.},
year = {2006},
publisher = {The Eurographics Association},
ISBN = {3-905673-58-4},
DOI = {10.2312/LocalChapterEvents/ItalianChapConf2006/241-246}
}