Medical Image Compression and Encryption Using Adaptive Arithmetic Coding, Quantization Technique and RSA in DWT Domain

Authors

DOI:

https://doi.org/10.24996/ijs.2022.63.5.38

Keywords:

Compression, Encryption, Medical Image, RSA, PSNR, Quantization, Arithmetic Coding, DWT

Abstract

Nowadays, the advances in information and communication technologies open the wide door to realize the digital world’s dream. Besides, within the clear scientific scope in all fields, especially the medical field, it has become necessary to harness all the scientific capabilities to serve people, especially in medical-related services. The medical images represent the basis of clinical diagnosis and the source of telehealth and teleconsultation processes. The exchange of these images can be subject to several challenges, such as transmission bandwidth, time delivery, fraud, tampering, modifying, privacy, and more. This paper will introduce an algorithm consisting a combination of compression and encryption techniques to meet such challenges in the medical image field. First, compression is done by applying the Adaptive Arithmetic Coding (AAC) technique and controllable frequency quantization process in the Discrete Wavelet Transform. After that, the encryption process is applied using RSA and SHA-256 algorithms to encrypt the compressed file and to create the digital signature. The performance analysis has shown that the algorithm can produce high compression ratio with good image quality, whereas range of PSNR near 45 dB and SIM is 0.88 as average values. For the security analysis, we have adopted data encryption and digital signature to guarantee the main data security services including integrity, authentication, and confidentiality, making the algorithm secure against passive or active attacks.

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Published

2022-05-25

How to Cite

Hussein, N. H. ., & Ali, M. A. (2022). Medical Image Compression and Encryption Using Adaptive Arithmetic Coding, Quantization Technique and RSA in DWT Domain. Iraqi Journal of Science, 63(5), 2279–2296. https://doi.org/10.24996/ijs.2022.63.5.38

Issue

Section

Computer Science

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