TY - GEN
T1 - Vector quantizers trained on small training sets
AU - Cohn, David
AU - Riskin, Eve A.
AU - Ladner, Richard
PY - 1993
Y1 - 1993
N2 - We examine how the performance of a memoryless vector quantizer (VQ) changes as a function of its training set size. By relating the training distortion of such a codebook to its test (true) distortion, we demonstrate that one may obtain 'good' codebooks at a fraction of the computational cost by training on a small random subset of the blocks in the target image.
AB - We examine how the performance of a memoryless vector quantizer (VQ) changes as a function of its training set size. By relating the training distortion of such a codebook to its test (true) distortion, we demonstrate that one may obtain 'good' codebooks at a fraction of the computational cost by training on a small random subset of the blocks in the target image.
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M3 - Conference contribution
AN - SCOPUS:0027277433
SN - 0780308786
T3 - Proceedings of the 1993 IEEE International Symposium on Information Theory
SP - 176
BT - Proceedings of the 1993 IEEE International Symposium on Information Theory
T2 - Proceedings of the 1993 IEEE International Symposium on Information Theory
Y2 - 17 January 1993 through 22 January 1993
ER -