By Topic

VQ index coding for high-fidelity medical 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
$31 $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

3 Author(s)
Wen Jiang ; Dept. of Inf. Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong ; Xiaolin Wu ; Wai Yin Ng

In order to obtain the high-fidelity medical compressed images, a new compression scheme is proposed. Based on the stringent requirements on lossy medical image compression, we refine the context modeling for a given class of medical images and utilize the conditional entropy coding of the VQ index (CECOVI) scheme to code the MR head images. The experimental results show that the image-type-dependent CECOVI can achieve better rate-distortion performance than the state-of-art wavelet image coder SPIHT. This also implies that incorporating the conditional entropy coding strategy into the VQ process is an appropriate way for high-fidelity medical image compression

Published in:

Image Processing, 1997. Proceedings., International Conference on  (Volume:3 )

Date of Conference:

26-29 Oct 1997