An Improved Image Re-indexing Technique by Self Organizing Motor Maps

  • Sebastiano Battiato
  • Francesco Rundo
  • Filippo Stanco
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5646)


The paper presents a novel Motor Map neural network for re-indexing color mapped images. The overall learning process is able to smooth the local spatial redundancy of the indexes of the input image. Differently than before, the proposed optimization process is specifically devoted to re-organize the matrix of differences of the indexes computed according to some predefined patterns. Experimental results show that the proposed approach achieves good performances 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.


Input Image Reward Function Indexing Scheme Lossless Compression Current Entropy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Sebastiano Battiato
    • 1
  • Francesco Rundo
    • 1
  • Filippo Stanco
    • 1
  1. 1.Dipartimento di Matematica e InformaticaUniversity of CataniaCataniaItaly

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