AN ENHANCED APPROACH UTILIZING AN OPTIMIZED DISCRETE WAVELET TRANSFORM FOR IMAGE STEGANOGRAPHY IN MEDICAL IMAGING

Hayder A.  Hadi; Haider S.  Al-Mumen; Mustafa R.  Ismael

doi:10.30572/2018/KJE/160422

Authors

Hayder A. Hadi Master's degree student, Department of Electrical Engineering, College of Engineering, University of Babylon, Iraq
Haider S. Al-Mumen Asst. Prof. Dr. Department of Electrical Engineering, College of Engineering, University of Babylon, Iraq
Mustafa R. Ismael Asst. Prof. Dr. Department of Electrical Engineering, College of Engineering, University of Babylon, Iraq

DOI:

https://doi.org/10.30572/2018/KJE/160422

Keywords:

Image Steganography, Wavelet Transform, Particle Swarm Optimization, Medical Image, Image Coding

Abstract

Image steganography constitutes a specific form of steganography wherein an image is employed as the concealing medium. Medical Image Steganography represents a distinctive subfield within the broader domain of Image Steganography. The safeguarding and confidentiality of sensitive patient data necessitate heightened scrutiny and scholarly investigation. Consequently, numerous techniques have been introduced over the past twenty years aimed at concealing patient information through the utilization of image steganography. In the present study, a new methodology is introduced for medical image steganography, leveraging Discrete Wavelet Transform (DWT) in conjunction with Particle Swarm Optimization (PSO). A Low-Density Parity Check was employed to encode the medical data prior to its concealment within the cover medical image. The experimental analysis was conducted on four distinct medical imaging modalities, namely X-ray, MRI, CT scan, and Ultrasound images, with the evaluation of performance based on metrics such as Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), and Structural Similarity Index Measure (SSIM). The findings of this investigation suggest that the PSO algorithm significantly enhances the efficacy of steganography, particularly when integrated with DWT techniques

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