High robustness watermark method based on singular value decomposition and discrete cosine transform

Abstract

The invention discloses a high robustness watermark method based on singular value decomposition and discrete cosine transform, which is characterized by comprising the following steps of: firstly, performing Arnold scrambling on a binary watermark image; then, selecting a sub-block to be embedded through discrete cosine transform according to mean square deviation; and then, embedding the watermark by using the discrete cosine transform coefficient of the sub-block for the effect of transform domain attach; finally, randomly selecting a position to embed a time-space domain for a region not embedded with watermark. In the method, a gray level image is embedded in the binary watermark, the attacks of time-space domain and transform domain are well resisted, and a high robustness method isprovided for the application of digital watermark.

Description

technical field [0001] The invention relates to a highly robust watermarking method, belonging to the fields of image processing and copyright protection. Background technique [0002] In the implicit watermarking technology, according to the method of embedding, it can be divided into two categories: time-space domain embedding and transform domain embedding. The watermark technology using singular value decomposition is involved in these two categories. Among these digital watermarking methods using singular value decomposition, according to the different embedding methods, the watermark embedding using singular value decomposition can be divided into Embedding of matrices and embedding using singular vector matrices. Because of the stability of singular values, most current methods are based on the embedding of singular value matrices. The embedding method based on the singular value matrix can be divided into the following three categories: modifying the singular value...

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Problems solved by technology

There are also defects in the method of using the singular vector matrix to embed the watermark. When the singular vector matrix is ​​modified, only the purpose of embedding the watermark is realized, but the orthonormality of the column vectors of the matrix is ​​destroyed, so that the modified singular vector matrix is ​​no longer orthogonal

After applying this matrix to the inverse transformation of the singular value decomposition to obtain the host image after embedding the watermark, in the step of extracting the watermark, it is also necessary to perform a singular value decomposition on the host image, and the singular vector matrix obtained at this time must still obey the singular value decomposition The principle of is still an orthogonal matrix, and the modification made in the step of embedding the watermark may disappear, which affects the robustness of the watermark extraction

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