Finite‐state entropy‐constrained vector quantiser for audio modified discrete cosine transform coefficients uniform quantisation
Sumxin Jiang, Rendong Yin, Peilin Liu · IET Signal Processing · 2015
In this paper, an entropy‐constrained vector quantiser (ECVQ) scheme with finite memory, called finite‐state ECVQ (FS‐ECVQ), is presented. This scheme consists of a finite‐state vector quantiser (FSVQ) and multiple component ECVQs. By utilising the FSVQ, the inter‐frame dependencies within source sequence can be effectively exploited and no side information needs to be transmitted. By employing the ECVQs, the total memory requirements of FS‐ECVQ can be efficiently decreased while the coding performance is improved. An FS‐ECVQ, designed for the modified discrete cosine transform coefficients coding, was implemented and evaluated based on the unified speech and audio coding (USAC) scheme. Results showed that the FS‐ECVQ achieved reduction of the total memory requirements by 92.3%, compared with the encoder in USAC working draft 6 (WD6), and over 10%, compared with the encoder in USAC final version (FINAL), while maintaining coding performance similar to FINAL, which was about 4% better than that of WD6.