Wavelet Based Multipurpose Color Image Watermarking by Using Dual Watermarks with Human Vision System Models

  • Authors:
  • Min-Jen Tsai;Chih-Wen Lin

  • Affiliations:
  • -;-

  • Venue:
  • IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
  • Year:
  • 2008

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Abstract

In this study, we propose a complete architecture based on digital watermarking techniques to solve the issue of copyright protection and authentication for digital contents. We apply visible and semi-fragile watermarks as dual watermarks where visible watermarking is used to establish the copyright protection and semi-fragile watermarking authenticates and verifies the integrity of the watermarked image. In order to get the best tradeoff between the embedding energy of watermark and the perceptual translucence for visible watermark, the composite coefficients using global and local characteristics of the host and watermark images in the discrete wavelet transform (DWT) domain is considered with Human Vision System (HVS) models. To achieve the optimum noise reduction of the visibility thresholds for HVS in DWT domain, the contrast-sensitive function (CSF) and noise visible function (NVF) of perceptual model is applied which characterizes the global and local image properties and identifies texture and edge regions to determine the optimal watermark locations and strength at the watermark embedding stage. In addition, the perceptual weights according to the basis function amplitudes of DWT coefficients is fine tuned for the best quality of perceptual translucence in the design of the proposed watermarking algorithm. Furthermore, the semi-fragile watermark can detect and localize malicious attack effectively yet tolerate mild modifications such as JPEG compression and channel additive white Gaussian noise (AWGN). From the experimental results, our proposed technique not only improves the PSNR values and visual quality than other algorithms but also preserves the visibility of the watermark visible under various signal processing and advanced image recovery attacks.