Learning Tree-structured Vector Quantization for Image Compression

  title={Learning Tree-structured Vector Quantization for Image Compression},
  author={Jianhua Xuan and ulay Adal},
Kohonen's self-organizing feature map (KSOFM) is an adaptive vector quantization (VQ) scheme for progressive code vector update. However, KSOFM approach belongs to unconstrained vector quantization, which suuers from exponential growth of the codebook. In this paper, a learning tree-structured vector quantization (LTSVQ) is presented for overcoming this drawback, which is based on competitive learning (CL) algorithm. LTSVQ algorithm is computationally very eecient, easy to implement and… CONTINUE READING


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