Abstract
With the growth of multimedia systems in distributed environments, the research of multimedia security as well as multimedia copyright protection becomes an important issue. As a potential and effective way to solve this problem, digital watermarking becomes a very active research area of signal and information processing. Many watermark algorithms have been proposed to address this issue of ownership identification. Discrete Cosine Transform (DCT) based spread-spectrum watermarking is one of the famous techniques. Another possible domain for watermark embedding is the wavelet domain. One of the many advantages over the Discrete Wavelet Transform (DWT) is that more accurately model aspects of the human visual system (HVS). In this paper a proposed algorithm is defined based on the combination between the benefits provides by using wavelet domain and profits of Code division multiple access (CDMA) spread-spectrum technique. A pseudo-random sequence (key) that related to hidden message is embedded into the significant DWT coefficients of a cover image to produce a watermarked image. Experimental results demonstrate that the proposed algorithm is perceptual invisible and robust against many attacks such as lossy image compression and Additive White Gaussian Noise (AWGN). Keywords: digital watermark, wavelet transform, CDMA technique.
Highlights
As multimedia data becomes wide spread, such as on the internet, there is a need to prevent the illegal copying, forgery and distribution of such data.Many approaches are available for protecting digital data; these include encryption, authentication and time stamping
There is a push toward the use of wavelets in signal processing and analysis in place of the discrete cosine transform (DCT), which is used in the jpeg standard for image compression
A pseudo-random sequence that related to hidden message is embedded into the significant Discrete Wavelet Transform (DWT) coefficients of a cover image to produce a watermarked image, and the message is retrieved by calculating the similarity function between the key and DWT coefficients of the watermarked image
Summary
As multimedia data becomes wide spread, such as on the internet, there is a need to prevent (or at least deter) the illegal copying, forgery and distribution of such data (digital images, video and audio). Based on the work of Cox [5] in the DCT domain, Kim [7] utilizes DWT coefficients of all subbands including the approximation image to embed a random Gaussian distributed watermark sequence in the whole image. Kundur [9] is embedding a binary watermark by modifying the amplitude relationship of three transform-domain coefficients from distinct detail subbands of the same resolution level of the host image. The security of this scheme lies entirely in the pseudo-random selection of coefficient locations. To strengthen the blind watermark extraction process, Kundur resorts to repetition and a reference mark
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