Fast image vector quantization using a modified competitive learning neural network approach

@article{Li1997FastIV,
  title={Fast image vector quantization using a modified competitive learning neural network approach},
  author={Robert Y. Li and Earnest Sherrod and Jung Hyun Kim and Gao Pan},
  journal={Int. J. Imaging Systems and Technology},
  year={1997},
  volume={8},
  pages={413-418}
}
The basic goal of image compression through vector generates the address of the codevector specified by Q(x) ; and quantization (VQ) is to reduce the bit rate for transmission or data a decoder, which uses this address to generate the codevector y . storage while maintaining an acceptable fidelity or image quality. The The signal-noise-ratio (SNR) is usually used to measure the fiadvantage of VQ image compression is its fast decompression by delity or quality of recovered image [4,15]. One… CONTINUE READING
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