Article révisé par les pairs
| Résumé : | We present a new algorithm for complexity-distortion optimization in tree-structured vector quantizers (TSVQ). The algorithm allows the user to specify the average rate and computational complexity budgets R and C, measured in bits and multiplications per sample, respectively. The output is an optimal - in a sense to be specified - TSVQ satisfying the constraints. The complexity budget is lower-bounded by the complexity of a binary TSVQ and upper-bounded by the complexity of a full-search entropy-constrained vector quantizer. Experimental results for synthetic and natural sources are given. © 2002 Elsevier Science B.V. All rights reserved. |
