Title: Wavelet packet transform-based medical image multiple watermarking with independent component analysis extraction
Authors: Nanmaran Rajendiran; Thirugnanam Gurunathan; Mangaiyarkarasi Palanivel
Addresses: Department of Electronics and Instrumentation Engineering, Annamalai University, Tamilnadu, India ' Department of Electronics and Instrumentation Engineering, Annamalai University, Tamilnadu, India ' Department of Electronics and Instrumentation Engineering, Annamalai University, Tamilnadu, India
Abstract: Rapid growth of internet in all aspects of life has led to the easy availability of the digital data to everyone. E-commerce, telemedicine, etc., are among the many applications of internet. Telemedicine is a crucial field where internet finds application. Healthcare professionals use internet to transmit and receive medical data. Thus the medical images can be shared, processed and transmitted through computer networks. All patient records, linked to the medical secrecy, must be confidential. Because of the importance of the security issues in the management of medical information, there is a need to develop watermarking techniques for protecting medical images. In this paper, colour medical image watermarking methods rely on wavelet packet transform (WPT) and extraction using independent component analysis (ICA). For watermark extraction, Pearson ICA is applied as it attains the new trait is that it not entail the renovation procedure in watermark extraction. The grades show that projected method is vigorous beside attacks such as Gaussian noise, salt and pepper noise, rotation and translation. The performance measures like PSNR, similarity measure and normalised correlation are assessed to confirm the robustness of the scheme.
Keywords: discrete wavelet transform; image watermarking; independent component analysis; ICA; Pearson ICA; wavelet packet transform; WPT.
DOI: 10.1504/IJMEI.2020.108236
International Journal of Medical Engineering and Informatics, 2020 Vol.12 No.4, pp.322 - 335
Received: 08 Nov 2017
Accepted: 16 Jun 2018
Published online: 07 Jul 2020 *