Compressive Sensing Theory for Improving the Robustness and the Security of the Discrete Wavelet Transform-Singular Value Decomposition Watermarking Scheme

Rasha Shoitan,Sawsan Morkos Gharghory

doi:10.3844/jcssp.2021.414.426

Rasha Shoitan, Sawsan Morkos Gharghory

Open Access

https://doi.org/10.3844/jcssp.2021.414.426

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Abstract

Digital watermarking has been suggested as a solution to protect copyright and ownership of digital images. The effective watermarking scheme should satisfy imperceptibility, robustness, capacity and security requirements. In this research, the security issue and the lack of reconstruction quality of the watermark logo of the integration of Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD) and Compressive Sensing (CS) watermark technique are addressed. Wilkinson measurement matrix is proposed to increase the robustness and improve the reconstruction quality of the watermark logo in the DWT and SVD based on the CS watermarking scheme. Additionally, the security issue of the SVD is solved by sending a scrambled compressed logo then extracting U, V matrices from this compressed logo at the decoder. The proposed method not only increases security but also reduces the size of the transmitted watermark logo. The robustness of the proposed algorithm is evaluated in the presence of different attacks like signal processing, compression, geometrical and noise attacks. The simulation results demonstrate that the proposed technique is more robust than the conventional techniques for all attacks, as well as its robust security. Moreover, the quality of the watermarked image is measured and the results show that the imaging performance of the proposed technique is approximately 0.7 to 4 dB better than that of the conventional methods. Consequently, the proposed watermarking scheme proves its ability to achieve the demands of security, imperceptibility and robustness against different attacks.

Highlights

The internet is considered a beneficial communication tool that recently can make people's lives much more manageable, it has terrible effects
The impact of the Wilkinson matrix on the performance of the proposed method is compared to the impact of the Gaussian matrix by comparing the proposed algorithm to Discrete Wavelet Transform (DWT)+Singular Value Decomposition (SVD)+Compressive Sensing (CS) based on Gaussian matrix algorithm
The idea of scramble compressed sensed watermark logo based on Wilkinson matrix is proposed

Summary

Introduction

The internet is considered a beneficial communication tool that recently can make people's lives much more manageable, it has terrible effects. Every day vast amounts of digital information are exposed to different types of attacks via the internet as data theft, spying, data corruption and denial of service attacks This leads to the risk of violating owner copyright and hampering digital content's authenticity; the owners of digital content need to provide a form of proof for their owners to preserve their ownership rights. Shannon-Nyquist theorem is the most important theorem that sets a limit to the sampling rate, guaranteeing recovery of the signal. The design of the measurement matrix is an important issue in compressive sensing since data recovery depends on how well the limited measurements provide information about the structure of the signal. These matrices reduce the quality of the reconstructed image from CS

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Conclusion