Digital Spread-Spectrum Watermarking Technique Based On M-Sequence

With the rapid enhancement of the compute ability and the fast development of Internet, the security of personal message becomes dangerous more and more. Although the conventional data encryption techniques maybe partially prevent the work be unauthorized released, almost all the data encryption technologies are crisis with the rapid enhance of the deciphering technique. Most hackers are bursting to attack the encrypted data as long as they find it, so that the encrypted data and the original data are same hazard. Moreover, when we need to use the carrier data to check the validity and the authorized information while the carrier data is used in gear, the conventional data encrypt techniques is inefficient.The data hiding technique will reduce the dangers of the hidden data. Firstly, nobody can know the hidden data except the author. This will not blaze the other's excitements to attack. Secondly, the hidden data would not be gone round even if the carrier data were destroyed.Watermarking is a new practical information hiding technique, and has grown rapidly. Digital watermarking has been proposed as a solution to the problem of copyright protection of multimedia documents in networked environments. It makes possible to embed a watermark (such as identification data, serials number, text or image etc.) to multimedia documents allowing copyright protection, secret communication, document authentication and so on.In this paper, the issue of embedding watermarking Sequence into image is researched. From the point of view of information theory, the carrier image can beviewed for a channel, and the watermark for signal to be transmitted. In this paper, we discuss digital spread-spectrum watermarking technique based on m-sequence. With this method, each watermark bit is embedded in all wavelet coefficients of one tree, and the watermark strength is determined by the characteristic of human visual system. While extracting, ach watermark is extracted independently using correlation detection. In the last section, this algorithm is implemented in matlab, the experimental results indicate this algorithm is robust to Gaussian noise and sharpening, and the watermarked image is hard to be distinguished from the original image.