Abstract
A new hierarchal structure of the self-organizing map (SOM) with dynamic growth is presented and applied to codebook design in vector quantization (VQ) and image compression. The tree-structured approach for codebook design is motivated for reducing the high computational efforts in the training and image coding phases in traditional VQ algorithms. The DHSOM has the ability to self determine the structure of the network through heuristically rules, and its final structure reflects the variability of the data (image blocks). It is shown that training that training and coding times obtained with DHSOM algorithm are faster than conventional SOM and LBG algorithms, while the qualitative results are given.
Published Version
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