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Upfront Time Segmentation Methods for Transform Coding of Audio
We study a transform coder that employs a dynamic programming based rate-distortion optimization framework for time segmentation. Although this coder exhibits a high performance, its computational complexity makes it unfeasible for many practical applications. It is investigated whether upfront time segmentation can reduce computational complexity without a significant increase in perceptual distortion. Upfront time segmentation can be accomplished by replacing the rate-distortion cost functional with low-complexity cost measures, that are independent of bit rate and perceptual distortion. Through both quantitative and qualitative evaluation it is shown that dynamic programming based upfront time segmentation for minimization of perceptual entropy can be a viable alternative to rate-distortion optimal time segmentation.
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