Robust Digital Image Watermarking Based on Joint DWT-DCT

Abstract

In this paper, a new robust digital image watermarking algorithm based on Joint DWT-DCT Transformation is proposed. A binary watermarked logo is scrambled by Arnold cat map and embedded in certain coefficient sets of a 3-level DWT transformed of a host image. Then, DCT transform of each selected DWT sub-band is computed and the PN-sequences of the watermark bits are embedded in the middle frequencies coefficients of the corresponding DCT block. In extraction procedure, the watermarked image, which maybe attacked, is pre-filtered by combination of sharpening and Laplassian of Gaussian filters to increase distinction between host image and watermark information. Subsequently, the same procedures as the embedding process is used to extract the DCT middle frequencies of each sub-band. Finally, correlation between mid-band coefficients and PNsequences is calculated to determine watermarked bits. Experimental results show that high imperceptibility is provided as well as higher robustness against common signal processing attacks. In compare to current watermarking algorithms which are based on the joint of DWT-DCT, proposed system is achieved significantly higher robustness against enhancement and noise addition attacks.

Fuzzy Clustering Based Medical Image Watermarking

“…Amirgholipour et al proposed a combined DWT and discrete cosine transform (DCT) technique, where a scrambled logo was embedded in certain coefficient sets of 3-level DWT of host images [12]. They exploited the properties of both wavelet and cosine transform to embed watermark information in the most robust and imperceptible part of the image.…”

Entropy based Video Watermarking Scheme

“…It represents an image as a sum of sinusoids of varying magnitudes and frequencies [1,7]. For an input image, X, of size N x N the DCT coefficients for the transformed output image, Y, are computed according to (1).…”

“…However, DWT has been used in digital image and video watermarking more frequently due to its time/frequency decomposition characteristics and its resemblance to the theoretical models of the human visual system [7]. DWTbased watermarking algorithms could further be improved by combining DWT with DCT [6,7]. The combination of the two transforms namely the DWT and the DCT could compensate for the drawbacks of each other, thus resulting in effective watermarking.…”

“…Commonly used frequency-domain transforms are the Discrete Wavelet Transform (DWT), the Discrete Cosine Transform (DCT) and Discrete Fourier Transform (DFT). However, DWT has been used in digital image and video watermarking more frequently due to its time/frequency decomposition characteristics and its resemblance to the theoretical models of the human visual system [7]. DWTbased watermarking algorithms could further be improved by combining DWT with DCT [6,7].…”

“…Current digital watermarking techniques may be grouped into spatialdomain techniques and frequency-domain techniques. Compared to spatial domain watermarking techniques, frequency-domain watermarking techniques proved to be more effective in achieving the imperceptibility and robustness requirements of digital watermarking algorithms [6,7]. Commonly used frequency-domain transforms are the Discrete Wavelet Transform (DWT), the Discrete Cosine Transform (DCT) and Discrete Fourier Transform (DFT).…”