Integer wavelet decomposition for lossy image compression

Julien Reichel; Gloria Menegaz; Marcus J. Nadenau

doi:10.1117/12.365838

18 October 1999 Integer wavelet decomposition for lossy image compression

Julien Reichel, Gloria Menegaz, Marcus J. Nadenau

Proceedings Volume 3808, Applications of Digital Image Processing XXII; (1999) https://doi.org/10.1117/12.365838
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

Using the lifting step approach for wavelet decomposition, Sweldens has recently introduced a fully integer based filtering method. There are several advantages to such an approach, one of the most interesting is the possibility to use wavelets for efficient lossless coding. However, this scheme is also interesting in case of lossy compression, especially for 'real-time' or 'low-cost' applications. In the PC based world, integer operations are more efficient than their floating-point counterparts, allowing much faster processing. In case of hardware implementations, integer based arithmetic units are much cheaper than those capable of handling floating points. In terms of memory usage, integer decomposition reduces the demands on the system by at least a factor two. For these reasons, we are interested in considering integer based filtering for lossy image compression as well. This raises an important question: what additional losses, if any, occur when using integer based wavelet decompositions in place of the usual floating point approach? First we compare the compressed images using standard SNR and other simple metrics. Next we evaluate our results using visually weighted objective metrics. This allows us to fully evaluate integer wavelet decomposition when applied to lossy image compression across a range of bit rates, filter characteristics and image types.

Citation Download Citation

Julien Reichel, Gloria Menegaz, and Marcus J. Nadenau "Integer wavelet decomposition for lossy image compression", Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); https://doi.org/10.1117/12.365838

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