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Proceedings Paper

Mammogram compression using adaptive prediction
Author(s): Anthony John Maeder
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Paper Abstract

The JPEG lossless compression technique uses pixel value prediction based on the nearest neighbor pixel values. Usually a single predictor is used for the entire image. Recent work has shown that better compression performance can be achieved by choosing the predictors adaptively depending on the context of surrounding pixel or predictor values. This method is computationally lengthy and memory intensive. In mammograms the image contents can be separated into three distinct visual classes: background, smooth and textured, corresponding to three classes of predictors available in JPEG. This paper discusses an approach to exploiting the use of these classes directly for predictor choice.

Paper Details

Date Published: 27 April 1995
PDF: 8 pages
Proc. SPIE 2431, Medical Imaging 1995: Image Display, (27 April 1995); doi: 10.1117/12.207616
Show Author Affiliations
Anthony John Maeder, Queensland Univ. of Technology (Australia)


Published in SPIE Proceedings Vol. 2431:
Medical Imaging 1995: Image Display
Yongmin Kim, Editor(s)

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