Pseudorandom Noise Sequence of Digital Watermarking Algorithm based on Discrete Wavelet Transform us

Pseudorandom Noise Sequence of Digital

Watermarking Algorithm based on Discrete

Wavelet Transform using Medical Image

Ramesh Muthiya1, Gomathy Balasubramanian2, and Sundararajan Paramasivam3

1Department of Electronics and Communication Engineering, St.Martin’s Engineering College, India

2Department of Computer and Science Engineering, Bannari Amman Institute of Technology, India

3Department of Electronics and Communication Engineering, Sri Shakthi Institute of Engineering and Technology, India

Abstract: Owing to the development of latest technologies in the areas of communication and computer networks, present day businesses are moving to the digital world for effectiveness, convenience and security. There are a number of applications in healthcare industry like tele-consulting, tele-surgery and tele-diagnosis. Today’s healthcare involves some security risks as these provide new ways to store, access and distribute medical data. Watermarking can be seen as an additional tool for security measures. Pseudorandom noise sequence image watermarking algorithm which is blind (it does not require the presence of input image for detection) and robust is also analyzed. The watermarking scheme embeds the binary logo in the Discrete Wavelet Transform (DWT) domain as in the sub-band level. Consequently, the simulation results show that the proposed algorithm achieves higher security and robustness against various attacks like Set Partitioning in Hierarchical Trees (SPIHT) and JPEG compression, adding Gaussian noise and salt and pepper noise, Gaussian filtering and average filtering. The promising experimental results are Peak Signal-Noise Ratio (PSNR) and Normalized Correlation (NC) value is reported and also by using Compression Techniques (CT) scan and MRI medical images.

Keywords: Discrete wavelet transform, watermarking algorithm, pseudorandom noise sequence, peak signal-noise ratio, normalized correlation and medical images.

Received September 22, 2014; accepted December 23, 2014

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