Algorithm to Balance Compression and Signal Quality Using Novel Compressive Sensing in Medical Images

Abstract

Usage of compressive sensing plays a highly contributory role in compression, storage, and transmission in medical images even in presence of inherent complexities associated with radiological images. After reviewing the existing system, we found that existing techniques are less focused on medical images ignoring the complexities associated with it. Hence, this paper presents a very simple and novel transform-based technique where the performance of compressive sensing is enhanced using novel parameters of linear approximation, index ordering, along with number of low pass coefficient, and auxiliary measurement. The algorithm formulated by the proposed system is purely capable of minimizing L1-minimization. The outcome of the proposed system shows well balance between the compression ratio and signal quality in contrast to the existing technique of compressive sensing in medical images.