Variants of Golomb Coding and the n-ary Versions
Na Wang, Sian-Jheng Lin, Yunghsiang S. Han, Nenghai Yu
Abstract
Na Wang, Sian-Jheng Lin, Yunghsiang S. Han, Nenghai Yu
Abstract
Golomb coding is a type of entropy encoding scheme for geometric distributions. It consists of two parts, and both parts are coded with variable-length coding, which requires a higher computational effort than fixed-length coding schemes. To solve this issue, the first part of this article presents a variant of Golomb coding that uses fixed-length coding to code the first part. The simulations show that the proposed coding scheme has a higher throughput than Golomb coding, due to the reduction of arithmetic complexity. In the second part, we discuss the n-ary versions of Golomb coding and the proposed coding scheme.
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Golomb coding is a type of entropy encoding scheme for geometric distributions. It consists of two parts, and both parts are coded with variable-length coding, which requires a higher computational effort than fixed-length coding schemes. To solve this issue, the first part of this article presents a variant of Golomb coding that uses fixed-length coding to code the first part. The simulations show that the proposed coding scheme has a higher throughput than Golomb coding, due to the reduction of arithmetic complexity. In the second part, we discuss the n-ary versions of Golomb coding and the proposed coding scheme.
Key concepts: Golomb coding, Variable-length code, Shannon–Fano coding, Tunstall coding, Context-adaptive binary arithmetic coding, Entropy encoding, Context-adaptive variable-length coding, Coding (social sciences)