Energy-Based Split Vector Quantizer Employing Signal Representation in Multiple Transform Domains
✍ Scribed by Wasfy B. Mikhael; Venkatesh Krishnan
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 383 KB
- Volume
- 11
- Category
- Article
- ISSN
- 1051-2004
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✦ Synopsis
Vector quantization schemes are widely used for waveform coding of one-and multidimensional signals. In this contribution, a novel energybased, split vector quantization technique is presented, which represents digital signals efficiently as measured by the number of bits per sample for a predetermined signal reconstruction quality. In this approach, each signal vector is projected into multiple transform domains. In the learning mode, for a given transform domain representation, the transformed vector is split into subvectors (subbands) of equal average energy estimated from the transformed training vector ensemble. An equal number of bits is assigned to each subvector. A codebook is then designed for each equal energy subband of each transform domain representation. In the running mode, the coder selects codes from the domain that best represents the signal vector. The proposed multiple transform, split vector quantizer is developed and its performance is evaluated for both singlestage and multistage implementations. Several single transform vector quantizers for waveform coding exist, some of which employ energy-based bit allocation. Sample results using one-dimensional speech signals confirm the superior performance of the proposed scheme over existing single transform vector quantizers for waveform coding.