Structured Preex Codes for Quantized Low-shape-parameter Generalized Gaussian Sources Structured Preex Codes for Quantized Low-shape-parameter Generalized Gaussian Sources

نویسندگان

  • Jiangtao Wen
  • John D. Villasenor
چکیده

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

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تاریخ انتشار 1999