Multiresolution SVD Based Image Watermarking Scheme Using Noise Visibility Function

Swanirbhar Majumder
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Swanirbhar Majumder: Department of Electronics and Communications Engineering, North Eastern Regional Institute of Science and Technology (NERIST), Itanagar, India

International Journal of Applied Evolutionary Computation (IJAEC), 2017, vol. 8, issue 1, 38-48

Abstract: This paper presents a robust and imperceptible methodology of watermark embedding. It uses two vital techniques, firstly the Multi-Resolution Singular Value Decomposition (MR-SVD) and an image adaptive algorithm on the lines of the human visual system (HVS), called Noise Visibility Function (NVF). This is a special type of Singular Value Decomposition (SVD) with cell based operation for multi-resolution behavior like wavelets. So, by embedding the watermark in the Eigen values the robustness of the scheme is enhanced. While for the imperceptibility the NVF has been employed here. The optimal areas for embedding the watermark are characterized by it based on the local smooth or rough textures detected on the MR-SVD image based on the wavelet strength at sub bands. For imperceptibility, the algorithm has been tested on standard test images and different types of attacks for robustness to obtain encouraging results. This incorporates MR-SVD for the first time with HVS based NVF function. Together they produce better results.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jaec00:v:8:y:2017:i:1:p:38-48

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