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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Primary-Ambient Extraction Based on Channel Pair for 5.1 Channel Audio Using Least Square
verfasst von : Dingyan Song, Ge Gao, Yi Chen, Xi Hu
Erschienen in: Advances in Multimedia Information Processing – PCM 2017
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Abstract
According to the growth of reality demand of digital media, the 5.1 surround is widely used and researched. To further improve the listening experience of the 5.1 channel audio, the primary-ambient extraction (PAE) is introduced to facilitate flexible rendering in spatial audio reproduction. The common multichannel PAE approach is principle component analysis (PCA), which suffers from high extraction errors and long computation time. In this letter, we proposed a novel approach based on channel pair for 5.1 channel audio, which considers the five channels as a set of channel pairs. Then a linear estimation framework is applied at any one time to only one pair, which converts the problem of PAE into the estimation of weight matrix, thus the weight of each component can be computed by using the Least Square. The experimental results indicate that the novel approach significantly outperforms the existing approach PCA.