Abstract

This paper presents a novel lossless compression technique of the context-based adaptive arithmetic coding which can be used to further compress the quantized parameters in audio codec. The key feature of the new technique is the combination of the context model in time domain and frequency domain which is called time-frequency context model. It is used for the lossless compression of audio coding parameters such as the quantized modified discrete cosine transform (MDCT) coefficients and the frequency band gains in ITU-T G.719 audio codec. With the proposed adaptive arithmetic coding, a high degree of adaptation and redundancy reduction can be achieved. In addition, an efficient variable rate algorithm is employed, which is designed based on both the baseline entropy coding method of G.719 and the proposed adaptive arithmetic coding technique. Experiments show that the proposed technique is of higher efficiency compared with the conventional Huffman coding and the common adaptive arithmetic coding when used in the lossless compression of audio coding parameters. For a set of audio samples used in the G.719 application, the proposed technique achieves an average bit rate saving of 7.2% at low bit rate coding mode while producing audio quality equal to that of the original G.719.

Highlights

  • Natural digital audio signals require large bandwidth for transmission and enormous amounts of storage space

  • In our work on arithmetic coding, the entropy coding method of an adaptive arithmetic coding technique with a time-frequency plane context model was developed, which has led to the improvement of coding the quantized modified discrete cosine transform (MDCT) coefficients and the frequency band gains

  • This paper introduces an efficient variable rate algorithm for G.719 based on the proposed adaptive arithmetic coding together with the original Huffman coding module

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Summary

Introduction

Natural digital audio signals require large bandwidth for transmission and enormous amounts of storage space. When using the arithmetic coding to compress the coding parameters directly, the probability estimation based on the bitplane context model may not be suitable In this situation, the correlation of audio coding parameters leading to lower information entropy could be considered both in time and frequency domain which can be deeply investigated in theory and carefully designed in practice. A novel time-frequency plane context model will be given in this paper, and the adaptive arithmetic coding will be used directly for the audio coding parameters. In our work on arithmetic coding, the entropy coding method of an adaptive arithmetic coding technique with a time-frequency plane context model (both time and frequency domain are taken into account) was developed, which has led to the improvement of coding the quantized MDCT coefficients and the frequency band gains.

Modules of the novel adaptive entropy coding
Experimental results
Conclusions
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