  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

Computer Vision and Pattern Recognition