Mammogram compression using super-resolution

Authors:
Jun Zheng;Olac Fuentes;Ming-Ying Leung;Elais Jackson
Affiliations:
The University of Texas at El Paso, El Paso, Texas;The University of Texas at El Paso, El Paso, Texas;The University of Texas at El Paso, El Paso, Texas;Tennessee State University, Nashville, TN
Venue:
IWDM'10 Proceedings of the 10th international conference on Digital Mammography
Year:
2010

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Abstract

As mammography moves towards completely digital and produces prohibitive amounts of data, compression plays an increasingly important role Although current lossless compression methods provide very high-quality images, their compression ratios are very low On the other hand, several lossy compression methods provide very high compression ratios but come with considerable loss of quality In this work, we describe a novel compression method that consists of downsampling the mammograms before applying the encoding procedure, and applying super-resolution techniques after the decoding procedure to recover the original resolution image In our experiments, we examine the tradeoffs between compression ratio and image quality using this scheme, and show it provides significant improvements over conventional methods.