1981IRE Transactions on Communications SystemsRequires access

Compression of Black-White Images with Arithmetic Coding

Glen G. Langdon, J. Rissanen

Open publisher page 363 citations

Abstract

A new approach for black and white image compression is described, with which the eight CCITT test documents can be compressed in a lossless manner 20-30 percent better than with the best existing compression algorithms. The coding and the modeling aspects are treated separately. The key to these improvements is an efficient binary arithmetic code. The code is relatively simple to implement because it avoids the multiplication operation inherent in some earlier arithmetic codes. Arithmetic coding permits the compression of binary sequences where the statistics change on a bit-to-bit basis. Model statistics are studied from stationary, stationary adaptive, and nonstationary adaptive assumptions.

About this research paper

What this paper is about

A new approach for black and white image compression is described, with which the eight CCITT test documents can be compressed in a lossless manner 20-30 percent better than with the best existing compression algorithms. The coding and the modeling aspects are treated separately. The key to these improvements is an efficient binary arithmetic code. The code is relatively simple to implement because it avoids the multiplication operation inherent in some earlier arithmetic codes. Arithmetic coding permits the compression of binary sequences where the statistics change on a bit-to-bit basis. Model statistics are studied from stationary, stationary adaptive, and nonstationary adaptive assumptions.

Why it matters

OpenAlex reports 363 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

A new approach for black and white image compression is described, with which the eight CCITT test documents can be compressed in a lossless manner 20-30 percent better than with the best existing compression algorithms. The coding and the modeling aspects are treated separately. The key to these improvements is an efficient binary arithmetic code. The code is relatively simple to implement because it avoids the multiplication operation inherent in some earlier arithmetic codes. Arithmetic coding permits the compression of binary sequences where the statistics change on a bit-to-bit basis. Model statistics are studied from stationary, stationary adaptive, and nonstationary adaptive assumptions.

Key concepts: Arithmetic coding, Lossless compression, Context-adaptive binary arithmetic coding, Arithmetic, Context-adaptive variable-length coding, Data compression, Binary number, Computer science

Related papers

Back to paper searchBrowse research topicsOriginal source
Compression of Black-White Images with Arithmetic Coding — Research Paper | ScholarLens