Mammogram compression using adaptive prediction

Anthony John Maeder

doi:10.1117/12.207616

27 April 1995 Mammogram compression using adaptive prediction

Anthony John Maeder

Proceedings Volume 2431, Medical Imaging 1995: Image Display; (1995) https://doi.org/10.1117/12.207616
Event: Medical Imaging 1995, 1995, San Diego, CA, United States

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.

Citation Download Citation

Anthony John Maeder "Mammogram compression using adaptive prediction", Proc. SPIE 2431, Medical Imaging 1995: Image Display, (27 April 1995); https://doi.org/10.1117/12.207616

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