Multilevel magnetic resonance imaging compression using compressive sensing
In this study, a multilevel compressive sensing (CS) compression for magnetic resonance imaging (MRI) images is presented. The proposed algorithm divides the image into frames of equal size, transforms the pixels inside the frame into the sparse domain, and then applies the CS compression to each frame with different level of compression. Four levels of compression are suggested, based on how sparse is the information inside the frame. The proposed algorithm is evaluated using six real MRI images showing different parts of the human body. The experimental results show a significant improvement of 7.03 dB in peak-signal-to-noise ratio and 23.76% in compression level (CL) when compared with a uniform CL algorithm.