Improved techniques for lossless image compression with reversible integer wavelet transforms

N. Memon, X. Wu, B. L. Yeo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The past few years have seen an increasing interest in using reversible integer wavelets in image compression. Reversible integer wavelet image coders facilitate decompression from low bit rates all the way up to lossless reconstruction. However, in the past, specific implementations of such techniques, like S+P, could not match the lossless compression performance of state-of-the-art predictive coding techniques like CALIC. We demonstrate for the first time that reversible integer wavelets together with proper context modeling can match the lossless compression performance of CALIC. This can be done without increase in the essential complexity over S+P. Our findings present a strong argument for using subband coding as a unified, elegant approach for both lossy and lossless image compression. Specifically, in this paper we outline how to obtain significantly higher coding efficiency over S+P by utilizing better filters and better context modeling and entropy coding of wavelet coefficients.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing
PublisherIEEE Comp Soc
Pages891-895
Number of pages5
Volume3
StatePublished - 1998
EventProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) - Chicago, IL, USA
Duration: Oct 4 1998Oct 7 1998

Other

OtherProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3)
CityChicago, IL, USA
Period10/4/9810/7/98

Fingerprint

Image compression
Wavelet transforms
Entropy

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Cite this

Memon, N., Wu, X., & Yeo, B. L. (1998). Improved techniques for lossless image compression with reversible integer wavelet transforms. In IEEE International Conference on Image Processing (Vol. 3, pp. 891-895). IEEE Comp Soc.

Improved techniques for lossless image compression with reversible integer wavelet transforms. / Memon, N.; Wu, X.; Yeo, B. L.

IEEE International Conference on Image Processing. Vol. 3 IEEE Comp Soc, 1998. p. 891-895.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Memon, N, Wu, X & Yeo, BL 1998, Improved techniques for lossless image compression with reversible integer wavelet transforms. in IEEE International Conference on Image Processing. vol. 3, IEEE Comp Soc, pp. 891-895, Proceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3), Chicago, IL, USA, 10/4/98.
Memon N, Wu X, Yeo BL. Improved techniques for lossless image compression with reversible integer wavelet transforms. In IEEE International Conference on Image Processing. Vol. 3. IEEE Comp Soc. 1998. p. 891-895
Memon, N. ; Wu, X. ; Yeo, B. L. / Improved techniques for lossless image compression with reversible integer wavelet transforms. IEEE International Conference on Image Processing. Vol. 3 IEEE Comp Soc, 1998. pp. 891-895
@inproceedings{6560c22def64404a9d2f443f29fa919b,
title = "Improved techniques for lossless image compression with reversible integer wavelet transforms",
abstract = "The past few years have seen an increasing interest in using reversible integer wavelets in image compression. Reversible integer wavelet image coders facilitate decompression from low bit rates all the way up to lossless reconstruction. However, in the past, specific implementations of such techniques, like S+P, could not match the lossless compression performance of state-of-the-art predictive coding techniques like CALIC. We demonstrate for the first time that reversible integer wavelets together with proper context modeling can match the lossless compression performance of CALIC. This can be done without increase in the essential complexity over S+P. Our findings present a strong argument for using subband coding as a unified, elegant approach for both lossy and lossless image compression. Specifically, in this paper we outline how to obtain significantly higher coding efficiency over S+P by utilizing better filters and better context modeling and entropy coding of wavelet coefficients.",
author = "N. Memon and X. Wu and Yeo, {B. L.}",
year = "1998",
language = "English (US)",
volume = "3",
pages = "891--895",
booktitle = "IEEE International Conference on Image Processing",
publisher = "IEEE Comp Soc",

}

TY - GEN

T1 - Improved techniques for lossless image compression with reversible integer wavelet transforms

AU - Memon, N.

AU - Wu, X.

AU - Yeo, B. L.

PY - 1998

Y1 - 1998

N2 - The past few years have seen an increasing interest in using reversible integer wavelets in image compression. Reversible integer wavelet image coders facilitate decompression from low bit rates all the way up to lossless reconstruction. However, in the past, specific implementations of such techniques, like S+P, could not match the lossless compression performance of state-of-the-art predictive coding techniques like CALIC. We demonstrate for the first time that reversible integer wavelets together with proper context modeling can match the lossless compression performance of CALIC. This can be done without increase in the essential complexity over S+P. Our findings present a strong argument for using subband coding as a unified, elegant approach for both lossy and lossless image compression. Specifically, in this paper we outline how to obtain significantly higher coding efficiency over S+P by utilizing better filters and better context modeling and entropy coding of wavelet coefficients.

AB - The past few years have seen an increasing interest in using reversible integer wavelets in image compression. Reversible integer wavelet image coders facilitate decompression from low bit rates all the way up to lossless reconstruction. However, in the past, specific implementations of such techniques, like S+P, could not match the lossless compression performance of state-of-the-art predictive coding techniques like CALIC. We demonstrate for the first time that reversible integer wavelets together with proper context modeling can match the lossless compression performance of CALIC. This can be done without increase in the essential complexity over S+P. Our findings present a strong argument for using subband coding as a unified, elegant approach for both lossy and lossless image compression. Specifically, in this paper we outline how to obtain significantly higher coding efficiency over S+P by utilizing better filters and better context modeling and entropy coding of wavelet coefficients.

UR - http://www.scopus.com/inward/record.url?scp=0032311748&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032311748&partnerID=8YFLogxK

M3 - Conference contribution

VL - 3

SP - 891

EP - 895

BT - IEEE International Conference on Image Processing

PB - IEEE Comp Soc

ER -