Color Palette Images Re-indexing by Self Organizing Motor Maps

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. Categories and Subject Descriptors (according to ACM CCS): I.4.2 [Image processing and Computer Vision]: Compression (Coding)

• Type: Conference
• Year: 2006
• Where: EGITALY
• Authors: Sebastiano Battiato, Francesco Rundo, Filippo Stanco
• Keywords: Computer Graphics, EGITALY 2006, Neural Network, Palette Re-ordering, Palette Re-ordering Problem