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Proceedings Paper

Statisically lossless image compression for CR and DR
Author(s): Susan S. Young; Bruce R. Whiting; David H. Foos
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Paper Abstract

This paper proposes an image compression algorithm that can improve the compression efficiency for digital projection radiographs over current lossless JPEG by utilizing a quantization companding function and a new lossless image compression standard called JPEG-LS. The companding and compression processes can also be augmented by a pre- processing step to first segment the foreground portions of the image and then substitute the foreground pixel values with a uniform code value. The quantization companding function approach is based on a theory that relates the onset of distortion to changes in the second-order statistics in an image. By choosing an appropriate companding function, the properties of the second-order statistics can be retained to within an insignificant error, and the companded image can then be lossless compressed using JPEG-LS; we call the reconstructed image statistically lossless. The approach offers a theoretical basis supporting the integrity of the compressed-reconstructed data relative to the original image, while providing a modest level of compression efficiency. This intermediate level of compression could help to increase the conform level for radiologists that do not currently utilize lossy compression and may also have benefits form a medico-legal perspective.

Paper Details

Date Published: 26 May 1999
PDF: 14 pages
Proc. SPIE 3658, Medical Imaging 1999: Image Display, (26 May 1999); doi: 10.1117/12.349452
Show Author Affiliations
Susan S. Young, Eastman Kodak Co. (United States)
Bruce R. Whiting, Mallinckrodt Institute of Radiology/Washington Univ. (United States)
David H. Foos, Eastman Kodak Co. (United States)

Published in SPIE Proceedings Vol. 3658:
Medical Imaging 1999: Image Display
Seong Ki Mun; Yongmin Kim, Editor(s)

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