Title :
Structured prefix codes for quantized low-shape-parameter generalized Gaussian sources
Author :
Wen, Jiangtao ; Villasenor, John D.
Author_Institution :
Dept. of Electr. Eng., California Univ., Los Angeles, CA, USA
fDate :
5/1/1999 12:00:00 AM
Abstract :
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
Keywords :
Gaussian processes; entropy codes; image coding; quantisation (signal); redundancy; source coding; code efficiency; entropy coding; image coding; low computational complexity; quantized low-shape-parameter generalized Gaussian sources; quantizer parameters; redundancy bounds; structured prefix codes; Computational complexity; Entropy coding; Image coding; Laplace equations; Quantization; Shape; Source coding;
Journal_Title :
Information Theory, IEEE Transactions on
