An Efficient Framework to Protect Medical Images

Authors

  • Mamtha Mohan MSRIT -Autonomous
  • Suma K V MSRIT -Autonomous
  • Deepika B Banagar MSRIT -Autonomous

DOI:

https://doi.org/10.3991/ijoe.v18i04.27841

Keywords:

Bit Rate, Entropy, Gradient Adjusted Prediction, Median Edge Detector

Abstract


In this work, lossless compression is considered and an efficient Encryption–then-compression (ETC) scheme is proposed for medical images. A considerably good level of security is achieved by the proposed scheme where image encryption is operated in the prediction error domain.  In addition, reasonably good compression of the encrypted medical images is achieved. Comparison is done between Gradient adjusted prediction (GAP) & Median Edge Detector (MED) techniques and GAP is found to perform better with respect to PSNR, bit rate and entropy.  The average values of PSNR, bit rate and entropy in decibels for MED predictor are 10.8313, 3.7695 and 3.8624 respectively. Similarly, for GAP predictor, the average values of PSNR, bit rate and entropy in decibels are 11.9025, 4.0279 and 4.1286 respectively.

Author Biographies

Mamtha Mohan, MSRIT -Autonomous

Assistant Professor

Department of Electronics & Communication Engineering

Suma K V, MSRIT -Autonomous

Associate Professor

Department of Electronics & Communication Engineering

Deepika B Banagar, MSRIT -Autonomous

Department of Electronics & Communication Engineering

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Published

2022-03-22

How to Cite

Mohan, M., K V, S., & B Banagar, D. (2022). An Efficient Framework to Protect Medical Images. International Journal of Online and Biomedical Engineering (iJOE), 18(04), pp. 143–154. https://doi.org/10.3991/ijoe.v18i04.27841

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Section

Papers