Accelerated codebook searching in a SOM-based Vector Quantizer

Kohonen´s SOM algorithm has been used successfully by some researchers for designing codebooks. However, while performing an exhaustive search in a large codebook with high dimensional vectors, the encoder faces a significant computational barrier. Due to its topology preservation property, SOM holds a good promise of being utilized for fast codebook searching. In this paper we develop a method for fast codebook searching by exploiting the topology preservation property of SOM. This method performs non-exhaustive search of the codebook to find a good match for a input vector. The method is a general one that can be applied to various signal domains. In the present paper its efficacy is demonstrated with spatial vector quantization of gray-scale images.