Massively parallel lossless compression of medical images using least-squares prediction and arithmetic coding
Weinlich A, Rehm J, Amon P, Hutter A, Kaup A (2013)
Publication Language: English
Publication Status: Published
Publication Type: Conference contribution, Conference Contribution
Publication year: 2013
Pages Range: 1680-1684
Article Number: 6738346
Event location: Melbourne, VIC
ISBN: 9781479923410
DOI: 10.1109/ICIP.2013.6738346
Abstract
Medical imaging in hospitals requires fast and efficient image compression to support the clinical work flow and to save costs. Least-squares autoregressive pixel prediction methods combined with arithmetic coding constitutes the state of the art in lossless image compression. However, a high computational complexity of both prevents the application of respective CPU implementations in practice. We present a massively parallel compression system for medical volume images which runs on graphics cards. Image blocks are processed independently by separate processing threads. After pixel prediction with specialized border treatment, prediction errors are entropy coded with an adaptive binary arithmetic coder. Both steps are designed to match particular demands of the parallel hardware architecture. Comparisons with current image and video coders show efficiency gains of 3.3-13.6% while compression times can be reduced to a few seconds. © 2013 IEEE.
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How to cite
APA:
Weinlich, A., Rehm, J., Amon, P., Hutter, A., & Kaup, A. (2013). Massively parallel lossless compression of medical images using least-squares prediction and arithmetic coding. In Proceedings of the 2013 20th IEEE International Conference on Image Processing, ICIP 2013 (pp. 1680-1684). Melbourne, VIC, AU.
MLA:
Weinlich, Andreas, et al. "Massively parallel lossless compression of medical images using least-squares prediction and arithmetic coding." Proceedings of the 2013 20th IEEE International Conference on Image Processing, ICIP 2013, Melbourne, VIC 2013. 1680-1684.
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