In this paper, we present a scalable approach to lossless watermarking for audio signals. The proposed watermarking framework is built on a recently standardized two-layer scalableaudio coder advanced audio zip (AAZ)...
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In this paper, we present a scalable approach to lossless watermarking for audio signals. The proposed watermarking framework is built on a recently standardized two-layer scalableaudio coder advanced audio zip (AAZ) [1]. By embedding watermarks in both the core layer and enhancement layer bitstreams. in a special way, the watermark distortion in either layer is compensated by the watermark in the opposite layer. The proposed spread-spectrum-based solution overcomes both the problem of introducing noninvertible distortions in lossy watermark approaches and the problem of nonadaptive embedding in lossless watermarking approaches. Theoretic analysis and experiment results further confirm the validity of the proposed framework in terms of payload, robustness, data expansion property, and perceptual quality.
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.
In this paper, an in depth investigation and comparison of the performance obtainable with short wavelet filters for low bit rate perceptual audiocoding is presented. This a priori knowledge of the short wavelet filt...
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ISBN:
(纸本)0819425915
In this paper, an in depth investigation and comparison of the performance obtainable with short wavelet filters for low bit rate perceptual audiocoding is presented. This a priori knowledge of the short wavelet filters performance evaluation open new horizons in their usage, especially, when combined with the Moving Pictures Expert Group (MPEG-4) requirements for segmental signal to noise ratio (SSNR) scalable audio coding.
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