Abstract
Exp-Golomb codes are adopted by current image and video standards to perform entropy coding. But Exp-Golomb codes are sensitive to source parameters such as quantizer step size and pdf shape parameter. Under variable source parameters, the coding efficiency of Exp-Golomb codes falls drastically, as poor as 30% and even worse. The author presents a new class of codes, hybrid Golomb codes, based on Exp-Golomb codes and Golomb-Rice codes, which integrates the properties of two classes of codes and thus are more robust than Exp-Golomb codes when source parameters change frequently. In particular when quantizer step size is changing, the coding efficiency of hybrid Golomb codes is higher 10% than that of Exp-Golomb codes
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