New Frontiers in Communication and Intelligent Systems
Markov Random Field based Compression of Encrypted Medical Images
Authors: Vinoth Kumar C and Nirmala K
Publishing Date: 05-05-2022
ISBN: 978-81-95502-00-4
Abstract
Medical images are extensively used to convey information for further diagnosis. A large number of such images need to be stored in medical databases with assured security. Secure transmission of medical images requires a robust encryption and compression algorithm. There have been a few researches on the binary and grayscale encrypted and compressed images, despite the fact that there have been many studies on the non-encrypted-compressed images. On the other hand, low computational complexity and high security are not able to achieve by existing encryption image compression algorithms simultaneously. As a result, a method for compressing an encrypted image demands additional investigation in order to make optimal use of storage space while maintaining confidentiality. In order to overcome this issue, this study proposes a novel image encryption-then-compression (ETC) system based on 2D Compressive Sensing (2DCS) and the Markov random field (MRF) model. The objective is to achieve both minimal computing complexity and high security. In addition, the reconstructed image should have a significantly higher Peak Signal-to-Noise Ratio (PSNR).
Keywords
Markov random field, Encryption, Compression, Compressive sensing, Wavelet Transform.
Cite as
Vinoth Kumar C and Nirmala K, "Markov Random Field based Compression of Encrypted Medical Images", In: Rahul Srivastava and Aditya Kr. Singh Pundir (eds), New Frontiers in Communication and Intelligent Systems, SCRS, India, 2022, pp. 309-317. https://doi.org/10.52458/978-81-95502-00-4-32