【作者】 黄春明；

【导师】 陈常谦；

【作者基本信息】 福州大学 ， 通信与信息系统， 2005， 硕士

【摘要】 低码率感知音频编码利用了“感知不相干性”和“统计冗余度”来对音频信号进行压缩,以期以最少的比特数获得“透明音质”。AAC正是利用了这两种编码策略来大幅度地降低对音频信号进行压缩所需的数据量。MPEG-2 AAC已成为MPEG-4音频部分的核心标准,代表了当今最好的音频编码技术,是MP3指定的继任者。本文首先介绍了感知编码的基本原理,特别对心理声学模型作了重点描述,接着对AAC的各主要编码模块进行了深入的分析。在此基础上,本文对AAC标准建议的编码算法作了某些改进。在AAC中,比例因子用于对量化噪声进行整形,通过一种两层嵌套循环在码率和音质之间找到一个最佳平衡点。在AAC标准算法中,比例因子用的是霍夫曼编码,但用霍夫曼编码涉及到码书的计算、查找和存储等,特别当符号较多码书较大时,更为耗时和占用存储空间。而且,相对于霍夫曼编码,算术编码在某些方面拥有更优异的性能。因此我们尝试对MPEG-2 AAC中的比例因子应用自适应算术编码,以取代原先的霍夫曼编码,主要目的是在不损伤音质的前提下降低码率。自适应算术编码的性能很大程度上取决于概率模型的正确构造。一般的自适应模型只有在已编码符号数足够多的情况下,其概率模型才趋于准确。为了进一步挖掘自适应模型的潜能,针对音频编码的特点,我们提出了一种基于上下文的自适应模型,利用当前帧前面N帧已编码的比例因子的概率分布来对当前帧的比例因子进行编码。最后利用已有的软件平台,实现了AAC的编解码器,对将来进一步展开研究和实际应用打下基础。更多还原

【Abstract】 Low bit-rate perceptual audio coding exploits perceptual irrelevancies and statistical redundancies to compress audio signals, aiming at achieving transparent audio quality with a minimum number of bits. MPEG-2 AAC uses the two coding strategies mentioned above to significantly reduce the bit rate used to represent audio signals. It has been adopted as the core standard in the audio coding part of MPEG-4. Moreover, MPEG-2 AAC is regarded as the current state-of-the-art technology of audio compression, and it is designated as the MP3’s successor. Firstly, perceptual coding principles are introduced in this paper; The psycho-acoustic model is described in detail. Then, an in-depth study on the primary modules of AAC is presented. Finally, improvements on several algorithm parts involved in AAC standard are described. In the standard AAC, scalefactors are used to shape quantization noise. Via a nest of two iteration loops, the best tradeoff between the bit rate and audio quality is found. Scalefactors are encoded with Huffman coding. Huffman coding involves codebook design, search and storage. It may incur high computational complexity and storage requirement, especially when codebook size or number of symbols is large. As it is known, arithmetic coding outperforms Huffman coding in some aspects. Therefore, we make attempts to encode scalefactors with adaptive arithmetic coding instead of Huffman coding. The objective of our effort is to reduce bit rate while maintaining audio quality. Performance of adaptive arithmetic coding depends on accuracy of the involved statistical model. In general, adaptively statistical model becomes accurate when the coded symbols are enough. In order to improve the statistical accuracy, we proposed an adaptive model based on context and features of audio coding. Using our proposed model, the scalefactors of current frame are represented with the statistical distribution of the N preceding frames. Finally, we implement AAC encoder and decoder and their improved versions on a X-86 platform. What we have done may offer a solid foundation for further research and applications.更多还原