A combined scheme of pixel and block level splitting for medical image compression and reconstruction

Abstract

Medical images are very important source of information of human body diagnosis or therapy. These images contain huge amount of information which needs to be compressed to reduce the storage capacity issues. These images require lossless compression techniques to save the information. Another crucial issue in medical imaging is to reconstruct image efficiently without losing information. In order to achieve the reconstruction of medical image we present a new approach by introducing convex-smoothing problems. This approach is implemented by dividing the input image into sub-problems. According to this approach we divide the input image into sub-problems which are solved by using compressed sensing method. After achieving the output of compressed sensed image, this problem is passed to the iterative process of problem solver to reduce the time, computational complexity and reconstruction error. Proposed model is implemented using MATLAB tool and tested with medical images. Results are carried in terms of the PSNR, reconstruction error and time.