Effective sparse representation of X-Ray medical images

TL;DR

This paper introduces a sparse representation method for X-Ray images that significantly reduces data size while maintaining quality, with efficient processing and low memory use.

Contribution

It presents a novel sparse representation framework specifically designed for X-Ray images, optimizing data reduction and computational efficiency.

Findings

Enormous reduction in data set size needed for image representation

Maintains high image quality despite data reduction

Achieves fast processing with low memory requirements

Abstract

Effective sparse representation of X-Ray medical images within the context of data reduction is considered. The proposed framework is shown to render an enormous reduction in the cardinality of the data set required to represent this class of images at very good quality. The particularity of the approach is that it can be implemented at very competitive processing time and low memory requirements