A novel medical image compression using Ripplet transform

In spite of great advancements in multimedia data storage and communication technologies, compression of medical data remains challenging. This paper presents a novel compression method for the compression of medical images. The proposed method uses Ripplet transform to represent singularities along arbitrarily shaped curves and Set Partitioning in Hierarchical Trees encoder to encode the significant coefficients. The main objective of the proposed method is to provide high quality compressed images by representing images at different scales and directions and to achieve high compression ratio. Experimental results obtained on a set of medical images demonstrate that besides providing multiresolution and high directionality, the proposed method attains high Peak Signal to Noise Ratio and significant compression ratio as compared with conventional and state-of-art compression methods.