Near Optimal, Low Complexity Arithmetic Coding for Generalized Gaussian Sources
We propose a near optimal, asymmetrical, low complexity, block-based arithmetic coding algorithm for the prediction residuals produced by lossless or lossy audio compression algorithms. The analysis of real-world prediction residuals motivates the use of a modified two-sided continuous generalized Gaussian distribution, pdf(x)=c(p,s)*exp[-(|x|/s)^p], which is mapped to a discrete distribution. Closed form formulas and fast numerical estimates for the block parameters (p,s) are derived. Using a distribution property, precomputed probability tables are obtained for different values of p, independent of s. The compression performance is within 0.2% of a high complexity, symmetrical coder. For very low complexity codes, an alternate coding algorithm is also proposed, employing only bit output, with comparable performance.
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