Asymmetric numeral systems: entropy coding combining speed of Huffman coding with compression rate of arithmetic coding

TL;DR

Asymmetric numeral systems (ANS) offer a new entropy coding method that combines the speed of Huffman coding with the compression efficiency of arithmetic coding, enabling faster and more accurate data compression.

Contribution

The paper introduces ANS as a novel entropy coding approach that simplifies implementation, reduces computational cost, and can also be used for data encryption, outperforming traditional methods.

Findings

ANS achieves about 50% faster decoding than Huffman coding.

ANS provides compression rates similar to arithmetic coding.

ANS uses small tables for encoding, enabling efficient and potentially encrypted data compression.

Abstract

The modern data compression is mainly based on two approaches to entropy coding: Huffman (HC) and arithmetic/range coding (AC). The former is much faster, but approximates probabilities with powers of 2, usually leading to relatively low compression rates. The latter uses nearly exact probabilities - easily approaching theoretical compression rate limit (Shannon entropy), but at cost of much larger computational cost. Asymmetric numeral systems (ANS) is a new approach to accurate entropy coding, which allows to end this trade-off between speed and rate: the recent implementation [1] provides about $50\%$ faster decoding than HC for 256 size alphabet, with compression rate similar to provided by AC. This advantage is due to being simpler than AC: using single natural number as the state, instead of two to represent a range. Beside simplifying renormalization, it allows to put the entire behavior for given probability distribution into a relatively small table: defining entropy coding automaton. The memory cost of such table for 256 size alphabet is a few kilobytes. There is a large freedom while choosing a specific table - using pseudorandom number generator initialized with cryptographic key for this purpose allows to simultaneously encrypt the data. This article also introduces and discusses many other variants of this new entropy coding approach, which can provide direct alternatives for standard AC, for large alphabet range coding, or for approximated quasi arithmetic coding.