Palette re-ordering is an 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 is already known, obtaining an optimal re-indexing scheme is not a trivial task. In this paper, we provide a novel algorithm for palette re-ordering problem making use of a motor map neural network. 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.
|Titolo:||Self Organizing Motor Maps for Colour Mapped Image Re-Indexing|
|Data di pubblicazione:||2007|
|Citazione:||Self Organizing Motor Maps for Colour Mapped Image Re-Indexing / BATTIATO S; RUNDO F; STANCO F. - In: IEEE TRANSACTIONS ON IMAGE PROCESSING. - ISSN 1057-7149. - 16:12(2007), pp. 2905-2915.|
|Appare nelle tipologie:||1.1 Articolo in rivista|