Extension of wavelet compression algorithms to 3D and 4D image data: exploitation of data coherence in higher dimensions allows very high compression ratios

Li Zeng; Christian Jansen; Michael A. Unser; Patrick Hunziker

doi:10.1117/12.449734

5 December 2001 Extension of wavelet compression algorithms to 3D and 4D image data: exploitation of data coherence in higher dimensions allows very high compression ratios

Li Zeng, Christian Jansen, Michael A. Unser, Patrick Hunziker

Author Affiliations +

Proceedings Volume 4478, Wavelets: Applications in Signal and Image Processing IX; (2001) https://doi.org/10.1117/12.449734
Event: International Symposium on Optical Science and Technology, 2001, San Diego, CA, United States

Abstract

High resolution multidimensional image data yield huge datasets. For compression and analysis, 2D approaches are often used, neglecting the information coherence in higher dimensions, which can be exploited for improved compression. We designed a wavelet compression algorithm suited for data of arbitrary dimensions, and assessed its ability for compression of 4D medical images. Basically, separable wavelet transforms are done in each dimension, followed by quantization and standard coding. Results were compared with conventional 2D wavelet. We found that in 4D heart images, this algorithm allowed high compression ratios, preserving diagnostically important image features. For similar image quality, compression ratios using the 3D/4D approaches were typically much higher (2-4 times per added dimension) than with the 2D approach. For low-resolution images created with the requirement to keep predefined key diagnostic information (contractile function of the heart), compression ratios up to 2000 could be achieved. Thus, higher-dimensional wavelet compression is feasible, and by exploitation of data coherence in higher image dimensions allows much higher compression than comparable 2D approaches. The proven applicability of this approach to multidimensional medical imaging has important implications especially for the fields of image storage and transmission and, specifically, for the emerging field of telemedicine.

Citation Download Citation

Li Zeng, Christian Jansen, Michael A. Unser, and Patrick Hunziker "Extension of wavelet compression algorithms to 3D and 4D image data: exploitation of data coherence in higher dimensions allows very high compression ratios", Proc. SPIE 4478, Wavelets: Applications in Signal and Image Processing IX, (5 December 2001); https://doi.org/10.1117/12.449734

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