This paper presents Advanced audio Zip (AAZ), a fine grained scalable to lossless (SLS) audio coder that has recently been adopted as the reference model for MPEG-4 audio SLS work. AAZ integrates the functionalities;o...
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This paper presents Advanced audio Zip (AAZ), a fine grained scalable to lossless (SLS) audio coder that has recently been adopted as the reference model for MPEG-4 audio SLS work. AAZ integrates the functionalities;of high-compression perceptual audiocoding, line granular scalable audio coding, and lossless audiocoding in a single framework, and simultaneously provides backward compatibility to MPEG-4 Advanced audiocoding (AAC). AAZ provides the fine granular bit-rate scalability from lossy to lossless coding, and such a scalability is achieved in a perceptually meaningful way, i.e., better perceptual quality at higher bit-rates. Despite its abundant functionalities, AAZ only introduces negligible overhead in terms of lossless compression performance compared with a nonscalable, lossless only audio coder. As a result, AAZ provides a universal yet efficient solution for digital audio applications such as audio archiving, network audio streaming, portable audio playing, and music downloading which were previously catered for by several different audiocoding technologies, and eliminates the need for any transcoding system to facilitate sharing of digital audio contents across these application domains.
Embedded polar quantization can be useful for progressive transmission of circularly symmetric data, e.g., for fine-grain scalablecoding of parametric audio. Sets of constrained-resolution embedded quantizers are bui...
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Embedded polar quantization can be useful for progressive transmission of circularly symmetric data, e.g., for fine-grain scalablecoding of parametric audio. Sets of constrained-resolution embedded quantizers are built recursively by successive refinement processes, that are detailed for strict polar quantization and unrestricted polar quantization. The quadratic error minimization problem is solved using equations similar to those of Max, and the refinement algorithm can, in the unrestricted case, be simplified using a high-rate approximation. For Gaussian data, comparisons with reference non-embedded quantizers show that the embedding property comes at an often negligible cost in terms of rate-distortion performance.
audio streaming provides users with abundant music experiences. scalable audio coding technology makes such experience possible with optimal quality and low cost. In this paper, adaptive audio streaming based on MPEG-...
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ISBN:
(纸本)9781424487554
audio streaming provides users with abundant music experiences. scalable audio coding technology makes such experience possible with optimal quality and low cost. In this paper, adaptive audio streaming based on MPEG-4 scalable to lossless audiocoding (SLS) is introduced. A model based technology is proposed for adaptive audio streaming to achieve optimal streaming quality. This scheme adaptively allocates the constraint resource to each audio frame according to the characteristics of different frames. As a result, the quality variation of streaming is reduced according to the available network condition. This scheme has low computational complexity and low memory requirement.
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