
For vector quantization (VQ), it is extremely time-consuming to extract the similar codeword with input vector during the encoding process. In this paper, a novel algorithm based on Hadamard transform (HT) is proposed. Two inequalities derived after performing HT to all input vectors are used to early remove impossible codewords in the distortion computations stage. From the experimental results, it is shown that the proposed approach can largely decrease the computation time for achieving VQ coding with the same quality with full search algorithm. More specifically, compared with the DHSS algorithm, the proposed algorithm reduces the computational time by 25% to 61%. Compared with the Panpsilas algorithm, the proposed algorithm reduces the computational time by 60% to 70%. Compared with the Laipsilas algorithm, the proposed algorithm reduces the computational time by 42% to 55%. Compared with the HTPDE algorithm, the proposed algorithm reduces the computational time by 20% to 40%.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
