EZW, SPIHT and WDR Methods for CT Scan and X-ray Images Compression Applications

  • S. Saradha RaniEmail author
  • G. Sasibhushana Rao
  • B. Prabhakara Rao
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)


Scanning rate of medical image tools has been significantly improved owing to the arrival of CT, MRI and PET. For medical imagery, storing in less area and not losing its details are vital. So, an efficient technique is necessary for storing in a cost-effective way. In this paper, wavelet is employed to perform decomposition, and image is compressed using Embedded Zero-Tree Wavelet (EZW), Set Partitioning in Hierarchical Trees (SPIHT) and Wavelet Difference Reduction (WDR) algorithms. These algorithms are applied to compress X-ray and CT images, and compared using performance metrics. From results, it is seen that compression ratio is better in WDR for all the wavelets than SPHIT and EZW. High compression ratio, 82.47, is obtained with Haar and WDR combination for CT scan, whereas this is 32.89 for Biorthogonal and WDR combination for X-ray. The main objective of this paper is to find the optimal combination of wavelets and image compression techniques.


Wavelet transform SPIHT EZW WDR 



The author would like to thank GIMSR, Visakhapatnam, for providing lower abdomen CT scan and shoulder X-ray images to carry out the research work.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • S. Saradha Rani
    • 1
    Email author
  • G. Sasibhushana Rao
    • 2
  • B. Prabhakara Rao
    • 3
  1. 1.Department of Electronics and Communication EngineeringGITAMVisakhapatnamIndia
  2. 2.Department of Electronics and Communication EngineeringAU College of Engineering, Andhra UniversityVisakhapatnamIndia
  3. 3.Department of Electronics and Communication EngineeringJNTUKKakinadaIndia

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