By Topic

Applying wavelet transforms with arithmetic coding to radiological image compression

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Pongskorn Saipetch ; Dept. of Radiol. Sci., California Univ., Los Angeles, CA, USA ; B. K. T. Ho ; R. Panwar ; M. Ma
more authors

Radiological archives need the images to be compressed at a moderate compression ratio between 10:1 to 20:1 while retaining good diagnostic quality. We have developed a compression algorithm based on discrete wavelet transforms (DWTs) and arithmetic coding (AC) that satisfies those requirements. This new method is superior to the previously developed full frame discrete cosine transform (FFDCT) method, as well as the industrial standard developed by the joint photographic expert group (JPEG). Since DWT is localized in both spatial and scale domains, the error due to quantization of coefficients does not propagate throughout the reconstructed picture as in FFDCT. Because it is a global transformation, it does not suffer the limitation of block transform methods such as JPEG. The severity of the error as measured by the normalized mean square error (NMSE) and maximum difference technique increases very slowly with compression ratio compared to the FFDCT. Normalized nearest neighbor difference (NNND), which is a measure of blockiness, stays approximately constant, while JPEG NNND increases rapidly with compression ratio. Furthermore, DWT has an efficient finite response filter FlR implementation that can be put in parallel hardware. DWT also offers total flexibility in the image format; the size of the image does not have to be a power of two as in the case of FFDCT

Published in:

IEEE Engineering in Medicine and Biology Magazine  (Volume:14 ,  Issue: 5 )