Application of grammar-based codes for lossless compression of digital mammograms

Xiaoli Li; Srithar Krishnan; Ngok-Wah Ma

doi:10.1117/1.2178792

1 January 2006 Application of grammar-based codes for lossless compression of digital mammograms

Xiaoli Li, Srithar Krishnan, Ngok-Wah Ma

Author Affiliations +

Journal of Electronic Imaging, Vol. 15, Issue 1, 013021 (January 2006). https://doi.org/10.1117/1.2178792

Abstract

A newly developed grammar-based lossless source coding theory and its implementation was proposed in 1999 and 2000, respectively, by Yang and Kieffer. The code first transforms the original data sequence into an irreducible context-free grammar, which is then compressed using arithmetic coding. In the study of grammar-based coding for mammography applications, we encountered two issues: processing time and limited number of single-character grammar G variables. For the first issue, we discover a feature that can simplify the matching subsequence search in the irreducible grammar transform process. Using this discovery, an extended grammar code technique is proposed and the processing time of the grammar code can be significantly reduced. For the second issue, we propose to use double-character symbols to increase the number of grammar variables. Under the condition that all the G variables have the same probability of being used, our analysis shows that the double- and single-character approaches have the same compression rates. By using the methods proposed, we show that the grammar code can outperform three other schemes: Lempel-Ziv-Welch (LZW), arithmetic, and Huffman on compression ratio, and has similar error tolerance capabilities as LZW coding under similar circumstances.

©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Xiaoli Li, Srithar Krishnan, and Ngok-Wah Ma "Application of grammar-based codes for lossless compression of digital mammograms," Journal of Electronic Imaging 15(1), 013021 (1 January 2006). https://doi.org/10.1117/1.2178792

Published: 1 January 2006

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available