Encoding and Decoding Algorithms of ANS Variants and Evaluation of Their Average Code Lengths
Hirosuke Yamamoto, Ken-ichi Iwata

TL;DR
This paper thoroughly explains the encoding and decoding algorithms of Asymmetric Numeral Systems (ANS), analyzes their theoretical average code lengths, and discusses their high-performance data compression capabilities used in major tech companies.
Contribution
It provides a detailed explanation of ANS algorithms and a theoretical analysis of their average code lengths, enhancing understanding of their efficiency.
Findings
ANS achieves near-arithmetic coding compression performance
Theoretical analysis of average code lengths for ANS
ANS is widely adopted in major tech systems
Abstract
Asymmetric Numeral Systems (ANS) proposed by Jarek Duda are high-performance distortionless data compression schemes that can achieve almost the same compression performance as arithmetic codes with less arithmetic operations than arithmetic coding. The ANS is widely used in various practical systems like Facebook, Apple, Google, Dropbox, Microsoft, and Pixar, due to their high performance, but many researchers still lack much knowledge about the ANS. This paper thoroughly explains the encoding and decoding algorithms of the ANS, and theoretically analyzes the average code length achievable by the ANS.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
