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Differential Coding-Based Medical Image Compression

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Computer Aided Intervention and Diagnostics in Clinical and Medical Images

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 31))

Abstract

Modern trends of technology face the challenges of cost-effective massive data storage and transmission. Image compression is a master key for this issue. Basically, the process of image compression reduces redundant and irrelevant information from the original data resulting in reduced data file size. Vector quantization is a lossy image compression technique which helps to achieve higher compression with less computation complexity. The aim of the proposed work is to develop a novel medical image compression method that blends differential encoding and vector quantization (VQ). The basic idea is to transform the input image blocks into a set of difference vectors (difference between the each pixel intensity value and its respective mean). The difference vectors are normalized to preserve the sign and further quantized to generate the codebook. The algorithm is also investigated with other statistical moments like median and mode for finding the difference vectors. The experimental results with test medical images have demonstrated better performance of the proposed method when compared to similar methods.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Applications, The Gandhigram Rural Institute - Deemed to be University, Gandhigram, 624302, Tamil Nadu, India

    P. Chitra & M. Mary Shanthi Rani

Authors
  1. P. Chitra
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  2. M. Mary Shanthi Rani
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Corresponding author

Correspondence to M. Mary Shanthi Rani .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India

    J. Dinesh Peter

  2. Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, USA

    Steven Lawrence Fernandes

  3. Brazilian Computer Society, Aalcides Platiny Alves Batista , Porto Alegre, Rio Grande do Sul, Brazil

    Carlos Eduardo Thomaz

  4. School of Computer Science, University of KwaZulu-Natal, Durban, South Africa

    Serestina Viriri

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Chitra, P., Mary Shanthi Rani, M. (2019). Differential Coding-Based Medical Image Compression. In: Peter, J., Fernandes, S., Eduardo Thomaz, C., Viriri, S. (eds) Computer Aided Intervention and Diagnostics in Clinical and Medical Images. Lecture Notes in Computational Vision and Biomechanics, vol 31. Springer, Cham. https://doi.org/10.1007/978-3-030-04061-1_2

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  • DOI: https://doi.org/10.1007/978-3-030-04061-1_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04060-4

  • Online ISBN: 978-3-030-04061-1

  • eBook Packages: EngineeringEngineering (R0)

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