Name
Abstract | ||
|---|---|---|
Palette re-ordering is a well known and very effective ap- proach for improving the compression of color indexed im- ages. 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 triv- ial task. In this paper we provide a novel algorithm for palette re-ordering problem making use of a Motor Map neural net- work. Experimental results show the real effectiveness of the proposed method both in terms of compression ratio and zero- order entropy of local differences. Also its computational complexity is competitive with previous works in the field. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICIP.2007.4379506 | Image Processing, 2007. ICIP 2007. IEEE International Conference |
Keywords | Field | DocType |
computational complexity,data compression,image coding,image colour analysis,self-organising feature maps,color indexed image compression,compression ratio,computational complexity,image re-indexing,palette re-ordering problem,self organizing motor map neural network,spatial distribution,zero-order entropy,Color,Data compression,Entropy,Image coding,Multimedia computing,Neural networks | Computer vision,Texture compression,Pattern recognition,Computer science,Color Cell Compression,Compression ratio,Artificial intelligence,Artificial neural network,Data compression,Lossless compression,Computational complexity theory,Context-adaptive binary arithmetic coding | Conference |
Volume | ISSN | ISBN |
6 | 1522-4880 E-ISBN : 978-1-4244-1437-6 | 978-1-4244-1437-6 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Battiato, S. | 1 | 8 | 1.56 |
| Francesco Rundo | 2 | 24 | 7.39 |
| Filippo Stanco | 3 | 1 | 1.11 |