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A novel medical image compression using Ripplet transform

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Abstract

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.

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Authors and Affiliations

  1. Department of Information Technology, Karunya University, Coimbatore, India

    Sujitha Juliet

  2. School of Computer Science and Technology, Karunya University, Coimbatore, India

    Elijah Blessing Rajsingh

  3. Bharat Heavy Electricals Limited, Trichy, India

    Kirubakaran Ezra

Authors
  1. Sujitha Juliet
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  2. Elijah Blessing Rajsingh
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  3. Kirubakaran Ezra
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Correspondence to Sujitha Juliet.

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Juliet, S., Rajsingh, E.B. & Ezra, K. A novel medical image compression using Ripplet transform. J Real-Time Image Proc 11, 401–412 (2016). https://doi.org/10.1007/s11554-013-0367-9

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