Technical Report
نویسنده
چکیده
In rate-distortion theory it has been shown that vector quantization (VQ) outperforms its counterpart, scalar quantization (SQ), consistently [Shannon, 1959], [GRAY, 1998]. However the major problems that may prevent its wide acceptance in image compression applications is the computational complexity. The VQ compression system is highly asymmetry in that significantly more computing time is required for training and encoding than for decoding. This is because the training and encoding process involves many comparisons to look for the best representatives or codewords, whereas the decoder simply hashes the decoded vector according to the index of a codeword specifying its position in the codebook.
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