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Structured Prefix Codes for Quantized Low-Shape-Parameter Generalized Gaussian Sources

The highly peaked wide-tailed pdf's that are encountered in many image coding algorithms are often modeled using the family of generalized Gaussian (GG) pdf's. We study entropy coding of quantized GG sources using prefix codes that are highly structured, and which therefore involve low computational complexity. We provide bounds for the redundancy associated with applying these codes to quantized GG sources. We also explore code efficiency and code choice for a wide range of GG source and quantizer parameters.