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A low-complexity soft VLC decoder using performance modeling

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In this paper, we propose a scalable soft VLC decoder to greatly reduce overall design complexity. Generally, the soft VLC decoder needs to maintain many states for the correct decoding when the table size grows. We reduce the table size by using a symbol-merging scheme. We merge two symbols with the same prefix into one. Further. to achieve the optimal trade-off between performance and complexity, we propose a Black-Box model. In our model, we present a novel measurement of "symbol-alias" to improve the accuracy of performance estimation. Experimental results show that our scalable soft VLC decoder using performance modeling has more than 1 dB PSNR gain and offers better subjective quality compared to traditional VLC decoding.

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