CN117474742A - Color image digital watermarking method, system, device and storage medium - Google Patents
Color image digital watermarking method, system, device and storage medium Download PDFInfo
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Abstract
The invention discloses a digital watermarking method, a digital watermarking system, digital watermarking equipment and a digital watermarking storage medium for color images, which are characterized in that corresponding layered carrier images are obtained by utilizing gray values on R, G, B, H, S, I, L, U, V components of a Clifford algebraic representation color carrier image; scrambling the R, G, B, H, S, I, L, U, V nine components of the color watermark image to obtain a corresponding layered scrambling image; dividing each layered carrier image into a plurality of first image blocks, and transforming each first image block to obtain a corresponding first transformation matrix; respectively embedding each pixel point on each layered scrambling image into an intermediate frequency coefficient in a corresponding first transformation matrix to obtain a corresponding embedding matrix; and carrying out inverse transformation on each embedded matrix to obtain second image blocks embedded with the watermark, and combining all the second image blocks to obtain the color image added with the watermark. The invention has high operation efficiency, high invisibility and high robustness.
Description
Technical Field
The invention belongs to the technical field of image processing, and particularly relates to a color image digital watermarking method, a color image digital watermarking system, color image digital watermarking equipment and a color image digital watermarking storage medium.
Background
With the rapid development of internet and multimedia technologies, copyright protection and information security problems of digital products are getting more and more attention. The digital watermarking technology becomes an effective means for solving the problems, and also becomes a research hotspot for domestic and foreign scientific researchers.
In recent years, various watermarking methods have emerged, and digital watermarking methods can be classified into two main categories according to embedding methods: spatial domain digital watermarking methods and frequency domain (transform domain) digital watermarking methods. However, the spatial domain watermarking method has the problems of limited embedding capacity and low robustness to various attacks such as compression, scaling and the like, so that the application of the spatial domain watermarking method is relatively wide. The transform domain commonly used at present comprises discrete cosine transform DCT, discrete wavelet transform DWT, discrete Fourier transform DFT and the like, and the color models adopted by the methods mainly comprise RGB model, HIS model, YCbCr model, YIQ model and the like.
1. Color image watermarking method based on spatial domain
The spatial domain watermarking method is to directly embed watermark information into the spatial domain of the original carrier image, the simplest spatial domain watermarking method is to embed watermark information into the image, and randomly select the least significant bits of some pixels, but the method is easy to damage by low-pass filtering or JPEG compression and the like, and has poor robustness. In order to enhance the robustness of the watermark, jiang Gangyi et al propose a color image watermarking method based on YUV space, according to the difference of brightness and texture of the image, watermark information with different intensities is respectively embedded into the brightness and chromaticity channels, and although the method has certain resistance to signal processing such as shearing, filtering, JPEG compression and the like, the embedded information amount of the method is limited, and the robustness of the watermark can not be well ensured.
2. Color image watermarking method based on transform domain
Compared with the space domain method, the transform domain method adopts a spread spectrum communication technology, has the characteristics of good invisibility and robustness, is compatible with international compression standards and the like, and can fully utilize the human perception characteristic. The transform domain watermarking method has become the main stream of the current watermarking technology research, and has been developed to a certain extent in practical application, and the main transform domain watermarking method is as follows.
(1) DCT domain-based color image watermarking
The discrete cosine transform is the most studied of a plurality of watermarking methods by virtue of the advantages of simple calculation, easy realization, compatibility with the currently popular international compression standard and the like.
The DCT first needs to block the image, then carries out DCT transformation, and the DCT coefficient obtained after transformation is arranged from low frequency to high frequency according to the Zig-Zig order. The upper left corner of the DCT coefficient is a direct current low frequency coefficient and an alternating current low frequency coefficient, the middle part is an alternating current medium frequency coefficient, and the lower right corner is an alternating current high frequency coefficient. The high frequency part represents the noise part of the image, and the noise part is easily lost by signal processing such as lossy compression or filtering. Whereas the medium-low frequency part contains most of the energy of the image, the human vision is sensitive to the medium-low frequency part. The compression and processing of the general image keep the middle and low frequency parts of the image in order to ensure the visibility of the image.
(2) DWT domain-based color image watermarking
Wavelet analysis, which is a time-scale analysis method, has achieved good application effects in the engineering fields of signal processing (especially image processing), pattern recognition, geophysics and the like. In digital watermarking and information hiding, the DWT domain watermarking method has a wide prospect along with the use of wavelet transformation in JPEG2000 and MPEG-4 because the good space-time local characteristic of the wavelet transformation has a transformation mechanism which is extremely consistent with the HVS shielding characteristic. The watermarking method proposed in Shuai Zhen et al is to perform three-level wavelet decomposition on the blue component which is least sensitive to human eyes, then divide the low-frequency component into blocks according to the size of the watermark signal, and implement watermark embedding by adopting a repeated embedding technology.
(3) Color image watermarking method based on DFT domain
Such methods are to achieve watermark embedding by changing the magnitudes of some of the Discrete Fourier Transform (DFT) coefficients of the image or by modifying the phase values of the DFT transform. In order to meet both the invisibility and robustness of the watermark, the method of embedding the watermark on the amplitude of the DFT coefficient of the image is generally to select the intermediate frequency coefficient to embed the watermark.
The common digital watermarking methods are used for independently embedding each component into the watermark, have lower operation efficiency, and can improve the operation efficiency of an algorithm and keep the relation among all channels of the color image and greatly improve the robustness of the algorithm along with the first introduction of the quaternion theory into the digital watermarking field by S.J. Sangwine et al. After that, many researchers at home and abroad put forward some new watermarking algorithms by combining quaternion theory with various transformations. However, the method of quaternion theory can only process color images as a vector as a whole in three dimensions at most, and if the quaternion filter is higher than four dimensions, the quaternion filter must fail. The method is applied to digital watermarking of color images by combining eight-element high-dimensional theory with discrete cosine transform, considers an HIS model on the basis of an RGB model, realizes the embedding of the color watermark images by performing discrete eight-element cosine transform on color carrier images, and has better imperceptibility and robustness to various attacks such as scaling, noise, filtering, shearing, compression, rotation and the like. However, if one wants to include more color components for overall processing, i.e. higher than eight dimensions, the eight-element filter will also fail.
Disclosure of Invention
The invention aims to provide a color image digital watermarking method, a color image digital watermarking system, color image digital watermarking equipment and a color image digital watermarking storage medium, wherein the color image digital watermarking method, the color image digital watermarking system, the color image digital watermarking equipment and the color image digital watermarking storage medium are high in operation efficiency, invisibility and robustness.
The first aspect of the present invention provides a color image digital watermarking method, comprising:
acquiring a color watermark image and a color carrier image to be watermarked;
obtaining a layered carrier image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the Clifford algebraic representation color carrier image;
scrambling R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color watermark image to obtain a corresponding layered scrambling image;
dividing each layered carrier image into a plurality of first image blocks, and transforming each first image block by using a preset cosine transform formula to obtain a corresponding first transformation matrix;
respectively embedding each pixel point on each layered scrambling image into an intermediate frequency coefficient in a corresponding first transformation matrix to obtain a corresponding embedding matrix;
and carrying out inverse transformation on each embedded matrix by using a preset cosine inverse transformation formula to obtain corresponding second image blocks embedded with the watermark, and combining all the second image blocks to obtain the color image added with the watermark.
Optionally, the method further comprises:
obtaining a layered color image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color image after the watermark is added by the Clifford algebraic representation;
dividing each layered color image into a plurality of third image blocks, and transforming each third image block by using the preset cosine transform formula to obtain a corresponding second transformation matrix;
extracting a corresponding layered watermark image by using a second transformation matrix and a corresponding first transformation matrix in each layered color image;
and carrying out inverse scrambling on each layered watermark image to obtain a corresponding layered inverse scrambling image, and fusing all the layered inverse scrambling images to obtain a watermark extraction image.
Optionally, the extracting the corresponding layered watermark image by using the second transformation matrix and the corresponding first transformation matrix in each layered color image includes:
calculating each layered watermark image by adopting a watermark extraction formula, wherein the watermark extraction formula is as follows:
wherein w' (x, y) represents the value of the pixel (x, y) in the layered watermark image, alpha represents the energy value of the third image block, Coefficients representing the midpoints (p, s) of the second transformation matrix,/and>coefficients representing points (p, s) in the first transformation matrix.
Optionally, the preset cosine transform formula is:
where u is a unit Clifford algebra, modulo 1, and u 2 Is-1, f (X, Y) represents the value of the pixel point (X, Y) on the image by Clifford algebra to be subjected to cosine transform, X represents the number of pixels in the image row, Y represents the number of pixels in the image column, p represents the position of the midpoint (p, s) of the matrix in the row direction, s represents the position of the midpoint (p, s) of the matrix in the column direction, C (e) (p, s) represents coefficients of points (p, s) of the transform matrix obtained after the cosine transform;
transforming each first image block by using a preset cosine transform formula to obtain a corresponding first transformation matrix, including:
substituting each first image block serving as a Clifford algebraic representation image to be subjected to cosine transform into the preset cosine transform formula, and then calculating to obtain a corresponding first transformation matrix.
Optionally, the embedding each pixel point on each layered scrambled image into the intermediate frequency coefficient in the corresponding first transformation matrix to obtain a corresponding embedded matrix includes:
Embedding each pixel point on each layered scrambling image into an intermediate frequency coefficient in a corresponding first transformation matrix by using an embedding formula to obtain a corresponding embedding coefficient, wherein the embedding formula is as follows:
wherein alpha is i Representing the energy value of the hierarchically scrambled image, w (x, y) representing the value of the pixel (x, y) in the hierarchically scrambled image,intermediate frequency coefficients representing the first transformation matrix, +.>Coefficients representing the embedding matrix;
and forming a corresponding embedding matrix according to the embedding coefficients corresponding to each layered scrambling image.
Optionally, the preset cosine inverse transformation formula is:
where u is a unit Clifford algebra, modulo 1, and u 2 For-1, c (p, s) denotes the coefficient of the midpoint (p, s) of the embedded matrix to be subjected to the inverse cosine transform, X denotes the number of points in the row direction of the matrix, Y denotes the number of points in the column direction of the matrix, p denotes the position of the midpoint (p, s) in the row direction of the matrix, s denotes the position of the midpoint (p, s) in the column direction of the matrix, and f' (X, Y) denotes the value of the pixel point (X, Y) in the second image block obtained after the inverse cosine transform.
Performing inverse transformation on each embedded matrix by using a preset cosine inverse transformation formula to obtain a corresponding second image block embedded with the watermark, wherein the method comprises the following steps:
Substituting each embedded matrix into the preset cosine transform formula, and then calculating to obtain a corresponding second image block with the embedded watermark.
A second aspect of the present invention provides a color image digital watermarking system, comprising:
the image acquisition module is used for acquiring a color watermark image and a color carrier image to be watermarked;
the first-coefficient representation module is used for obtaining a layered carrier image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the Clifford algebraic representation color carrier image;
the watermark scrambling module is used for scrambling R, G, B, H, S, I, L, U, V nine components corresponding to each pixel point of the color watermark image to obtain a corresponding layered scrambling image;
the first transformation module is used for dividing each layered carrier image into a plurality of first image blocks, and transforming each first image block by using a preset cosine transformation formula to obtain a corresponding first transformation matrix;
the watermark embedding module is used for respectively embedding each pixel point on each layered scrambling image into the intermediate frequency coefficient in the corresponding first transformation matrix to obtain a corresponding embedding matrix;
And the inverse transformation module is used for carrying out inverse transformation on each embedded matrix by utilizing a preset cosine inverse transformation formula to obtain corresponding second image blocks embedded with the watermark, and combining all the second image blocks to obtain the color image added with the watermark.
Optionally, the method further comprises:
the second algebraic representation module is used for obtaining a layered color image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color image after the watermark is added by the Clifford algebraic representation;
the second transformation module is used for dividing each layered color image into a plurality of third image blocks, and transforming each third image block by utilizing the preset cosine transformation formula to obtain a corresponding second transformation matrix;
the watermark extraction module is used for extracting a corresponding layered watermark image by utilizing the second transformation matrix and the corresponding first transformation matrix in each layered color image;
and the watermark anti-scrambling module carries out anti-scrambling on each layered watermark image to obtain a corresponding layered anti-scrambling image, and fuses all the layered anti-scrambling images to obtain a watermark extraction image.
A third aspect of the invention provides a computer device comprising a memory storing a computer program and a processor implementing the steps of the method described above when the computer program is executed by the processor.
A fourth aspect of the invention provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method described above.
The technical scheme provided by the invention has the following advantages and effects: the R, G, B, H, I, S, L, U, V nine components of the color watermark image are scrambled, so that the security of the watermark is improved, then the R, G, B, H, I, S, L, U, V nine components of the color carrier image are integrally subjected to Clifford algebraic cosine transform, the operation efficiency is high, compared with a color image digital watermarking method based on discrete eight-element cosine transform and discrete quaternion cosine transform, the method has better invisibility and robustness, the layered scrambled image is embedded into each intermediate frequency coefficient of the color carrier image, and finally the color image containing the watermark is obtained by means of a preset cosine inverse transformation formula.
Drawings
FIG. 1 is a schematic flow chart of a color image digital watermarking method provided by the invention;
FIG. 2 is a color carrier image Lena used for experiments in an embodiment of the present invention;
FIG. 3 is a color carrier image Peppers used experimentally in the examples of the present invention;
FIG. 4 is a color watermark image used for experiments in an embodiment of the present invention;
FIG. 5 is an image Lena containing a watermark in an experiment of an embodiment of the invention;
FIG. 6 is a watermark image extracted from a watermark-containing image Lena in an embodiment of the invention;
FIG. 7 is a watermark-containing image Peppers in an experiment according to an embodiment of the invention;
FIG. 8 is a watermark image extracted from a watermarked image Peppers in an embodiment of the present invention;
FIG. 9 is a watermark extracted after various attacks on the watermark-containing image Lena in an experiment according to an embodiment of the invention;
FIG. 10 is a watermark extracted after various attacks by the watermark-containing image Peppers in an experiment according to an embodiment of the present invention;
fig. 11 is a block diagram of a color image digital watermarking system provided by the present invention;
fig. 12 is an internal structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
In order that the invention may be readily understood, a more particular description of specific embodiments thereof will be rendered by reference to specific embodiments that are illustrated in the appended drawings.
As used herein, the terms "first and second …" are used merely to distinguish between names and not to represent a particular number or order unless otherwise specified or defined.
The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items, unless specifically stated or otherwise defined.
The term "fixed" or "connected" as used herein may be directly fixed or connected to an element, or indirectly fixed or connected to an element.
As shown in fig. 1, the present embodiment provides a color image digital watermarking method, including:
and step 1, acquiring a color watermark image and a color carrier image to be watermarked.
And 2, obtaining a layered carrier image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the Clifford algebraic representation color carrier image.
Specifically, assume first (e 1 ，e 2 ，…e n ) Is a set of orthogonal bases of linear space on real number domain R, clifford algebra A n Is formed by (e) 1 ，e 2 ，…e n ) The tensed combination algebra satisfies:
e i e j ＝-e j e i ，1≤i≠j≤n，
wherein A is n The elements in (a) are called Clifford number, arbitrary x ε A n X has the form:
x＝λ 0 +∑λ A e A ，A＝(h 1 ，…，h p )，1≤h 1 ＜…＜h p ≤n，1≤p≤n，
obviously A n Is 2 n Algebra of the combination of dimensions but not of the exchange.
If Clif isford number x has the formX is referred to as a Clifford vector. For any x E A n The Clifford mode of x is defined as +.>In particular, the modulus of the Clifford vector x is
Then, coordinate axis e of nine-dimensional vector space is defined 0 ，e 1 ，e 2 ，e 3 ，e 4 ，e 5 ，e 6 ，e 7 ，e 8 The vector function in the space is defined again and is marked as f, and R, G, B, H, S, I, L, U, V component values corresponding to each pixel point of the color carrier image are used as corresponding numerical values on the imaginary part of f. Let the size of the color carrier image f (X, Y) be X Y, where X and Y indicate the position of the pixel in the matrix of rows and columns, X ε [0, X-1 ]]，y∈[0，Y-1]The Clifford algebra of the color carrier image f (x, y) is expressed as follows:
f(x，y)＝f R (x，y)e 0 +f G (x，y)e 1 +f B (x，y)e 2 +f H (x，y)e 3 +f S (x，y)e 4 +f I (x，y)e 5 +f L (x，y)e 6 +f U (x，y)e 7 +f V (x，y)e 8
wherein f R，G，B，H，S，I，L，U，V (x, y) are the gray values of the R, G, B, H, S, I, L, U, V component of each pixel in the color carrier image, i.e., f R (x, y) represents a layered carrier image of the Clifford algebraic representation of the color carrier image on the R component, f G (x, y) represents a layered carrier image of the Clifford algebraic representation of the color carrier image on the G component, f B (x, y) represents a layered carrier image of the Clifford algebraic representation of the color carrier image on the B component, f H (x, y) tableLayered carrier image showing Clifford algebraic representation of color carrier image on H component, f S (x, y) represents a layered carrier image of the Clifford algebraic representation of the color carrier image on the S component, f I (x, y) represents a layered carrier image of the Clifford algebraic representation of the color carrier image on the I component, f L (x, y) represents a layered carrier image of the Clifford algebraic representation of the color carrier image on the L component, f U (x, y) represents a layered carrier image of the Clifford algebraic representation of the color carrier image on the U component, f V (x, y) represents a layered carrier image of the Clifford algebraic representation of the color carrier image on the V component.
And step 3, scrambling R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color watermark image to obtain a corresponding layered scrambling image.
Specifically, in this embodiment, R, G, B, H, S, I, L, U, V components corresponding to each pixel of the color watermark image are scrambled by using Arnold transformation to obtain a corresponding layered scrambled image, where Arnold transformation is used to scramble positions of each pixel on the color watermark image to eliminate correlation between adjacent pixels of the color watermark image, and then function norm () in MATLAB software is used to calculate energy values α of the layered scrambled image corresponding to R, G, B, H, S, I, L, U, V nine components i (i＝1，2，…，9)，α 1 Representing the energy value, alpha, of the hierarchically scrambled image corresponding to the R component 2 Representing energy values, alpha, of a layered scrambled image corresponding to the G component 3 Representing the energy value, alpha, of the layered scrambled image corresponding to the B component 4 Representing energy values, alpha, of a hierarchically scrambled image corresponding to the H component S Representing the energy value, alpha, of a hierarchically scrambled image corresponding to the S component I Representing energy values, alpha, of a layered scrambled image corresponding to the G component L Representing the energy value, alpha, of the hierarchically scrambled image corresponding to the L component U Representing the energy value, alpha, of the hierarchically scrambled image corresponding to the U component V And represents the energy value of the hierarchically scrambled image corresponding to the V component.
And 4, dividing each layered carrier image into a plurality of first image blocks, and transforming each first image block by using a preset cosine transform formula to obtain a corresponding first transformation matrix.
Specifically, the preset cosine transform formula is:
where u is a unit Clifford algebra, modulo 1, and u 2 Is-1, f (X, Y) represents the value of the pixel point (X, Y) on the image by Clifford algebra to be subjected to cosine transform, X represents the number of pixels in the image row, Y represents the number of pixels in the image column, p represents the position of the midpoint (p, s) of the matrix in the row direction, s represents the position of the midpoint (p, s) of the matrix in the column direction, C (e) (p, s) represents coefficients of points (p, s) of the transform matrix obtained after the cosine transform;
transforming each first image block by using a preset cosine transform formula to obtain a corresponding first transformation matrix, including:
substituting each first image block serving as a Clifford algebraic representation image to be subjected to cosine transform into the preset cosine transform formula, and then calculating to obtain a corresponding first transformation matrix.
Specifically, the size of the first image block of 8× 8,u in the present embodiment can be expressed as:
u＝u 0 e 0 +u 1 e 1 +u 2 e 2 +u 3 e 3 +u 4 e 4 +u 5 e 5 +u 6 e 6 +u 7 e 7 +u 8 e 8 ，
according to the preset cosine transform formula, the first image block can be transformed from a spatial domain to a frequency domain, the first transform matrix is composed of 8×8 spectral coefficients, in other embodiments, the size of the first image block may be n×n, and the obtained first transform matrix is composed of n×n spectral coefficients; substituting each first image block as a Clifford algebraic representation image to be subjected to cosine transform into the preset cosine transform formula to perform discrete cosine transform, namely substituting each pixel point in the first image block into the preset cosine transform formula to obtain a corresponding frequency spectrum coefficient, and further obtaining a corresponding first transformation matrix.
And 5, respectively embedding each pixel point on each layered scrambling image into the intermediate frequency coefficient in the corresponding first transformation matrix to obtain a corresponding embedding matrix.
Specifically, the embedding each pixel point on each layered scrambled image into the intermediate frequency coefficient in the corresponding first transformation matrix to obtain the corresponding embedding matrix includes:
embedding each pixel point on each layered scrambling image into an intermediate frequency coefficient in a corresponding first transformation matrix by using an embedding formula to obtain a corresponding embedding coefficient, wherein the embedding formula is as follows:
wherein alpha is i Representing the energy value of the hierarchically scrambled image, w (x, y) representing the value of the pixel (x, y) in the hierarchically scrambled image,intermediate frequency coefficients representing the first transformation matrix, +.>Coefficients representing the embedding matrix;
and forming a corresponding embedding matrix according to the embedding coefficients corresponding to each layered scrambling image.
In the present embodiment of the present invention, in the present embodiment,intermediate frequency coefficient representing the first transformation matrix corresponding to the R component,/->Intermediate frequency coefficient representing the first transformation matrix corresponding to the G component,/->Intermediate frequency coefficient representing the first transformation matrix corresponding to the B component,/->Intermediate frequency coefficient representing the first transformation matrix corresponding to the H component, < > >Intermediate frequency coefficient representing the first transformation matrix corresponding to the S component,/->Intermediate frequency coefficients representing a first transformation matrix corresponding to the I component,intermediate frequency coefficient representing the first transformation matrix corresponding to the L component,/->Intermediate frequency coefficient representing the first transformation matrix corresponding to the U component,/->Intermediate frequency coefficient representing the first transformation matrix corresponding to the V component,/for the first transformation matrix>Coefficients representing the embedding matrix corresponding to the R component, < ->Coefficients representing the embedding matrix corresponding to the G component, +.>Coefficients representing the embedding matrix corresponding to the B component, +.>Coefficients representing the embedding matrix corresponding to the H component, < ->Coefficients representing the embedding matrix corresponding to the S component, < ->The coefficients representing the embedding matrix to which the 1 component corresponds,coefficients representing the embedding matrix corresponding to the L component, +.>Coefficients representing the embedding matrix corresponding to the U component, +.>The coefficients of the embedded matrix corresponding to the V component are represented by a frequency spectrum coefficient which is divided into a high frequency coefficient, a medium frequency coefficient and a low frequency coefficient, wherein the high frequency coefficient refers to a part with severe image change, namely the edge (outline) or noise and detail part of the image, mainly measures the edge and outline of the image, the medium frequency coefficient determines the basic mechanism of the image, and the main edge structure of the image is formed The low-frequency coefficient refers to a region with gentle image intensity transformation, namely a large flat region in an image, describes the main part of the image, is a comprehensive measure of the intensity of the whole image, and is obtained by substituting each pixel point of the layered scrambling image into an embedding formula, namely embedding each pixel point of the layered scrambling image into an intermediate frequency coefficient in a corresponding first transformation matrix to obtain a coefficient of a corresponding embedding matrix, and further obtaining the corresponding embedding matrix.
And 6, carrying out inverse transformation on each embedded matrix by using a preset cosine inverse transformation formula to obtain corresponding second image blocks embedded with the watermark, and combining all the second image blocks to obtain the color image added with the watermark.
Specifically, the preset inverse cosine transform formula is:
wherein C (p, s) represents a coefficient of a midpoint (p, s) of the embedded matrix to be subjected to the inverse cosine transform, X represents the number of points in the row direction of the matrix, Y represents the number of points in the column direction of the matrix, p represents the position of the midpoint (p, s) in the row direction of the matrix, s represents the position of the midpoint (p, s) in the column direction of the matrix, and f' (X, Y) represents the value of the pixel point (X, Y) in the second image block obtained after the inverse cosine transform.
Performing inverse transformation on each embedded matrix by using a preset cosine inverse transformation formula to obtain a corresponding second image block embedded with the watermark, wherein the method comprises the following steps:
substituting each embedded matrix into the preset cosine transform formula, and then calculating to obtain a corresponding second image block with the embedded watermark.
Specifically, u can be expressed as:
u＝u 0 e 0 +u 1 e 1 +u 2 e 2 +u 3 e 3 +u 4 e 4 +u 5 e 5 +u 6 e 6 +u 7 e 7 +u 8 e 8 ，
in this embodiment, according to the preset inverse cosine transform formula, an embedding matrix can be transformed from a frequency domain to a spatial domain, where the embedding matrix is composed of 8×8 spectral coefficients, so as to obtain a second image block with a size of 8×8; substituting each embedded matrix into the preset cosine inverse transformation formula as a matrix to be subjected to cosine inverse transformation, namely substituting each coefficient in the embedded matrix into the preset cosine inverse transformation formula to obtain a corresponding pixel value, further obtaining a corresponding second image block, and then combining all the second image blocks to obtain the color image added with the watermark.
In case a watermark needs to be extracted from said color image, the method of extracting the watermark comprises the steps of:
step 7, obtaining a layered color image of the corresponding Clifford algebraic representation, which is marked as f ', by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color image after watermark addition by the Clifford algebraic representation' 1 (x，y)、f′ 2 (x，y)、f′ 3 (x，y)、f′ 4 (x，y)、f′ 5 (x，y)、f′ 6 (x，y)、f′ 7 (x，y)、f′ 8 (x，y)、f′ 9 (x, y) respectively representing R, G, B, H, S, I, L, U componentsLayered color image corresponding to V component.
And 8, dividing each layered color image into a plurality of third image blocks, and transforming each third image block by using the preset cosine transform formula to obtain a corresponding second transformation matrix.
In the present embodiment, the third image block is also 8×8 in size, and each of the layered color images is divided into a plurality of third image blocks, which are denoted asr=1, 2, …, k, k represents the number of third image blocks, then will +.>Substituting a preset cosine transform formula to obtain a corresponding second transformation matrix, and marking the second transformation matrix as +.>
And 9, extracting the corresponding layered watermark image by using the second transformation matrix and the corresponding first transformation matrix in each layered color image.
In this embodiment, the first transformation matrix is denoted asSpecifically, the extracting the corresponding layered watermark image by using the second transformation matrix and the corresponding first transformation matrix in each layered color image includes:
calculating each layered watermark image by adopting a watermark extraction formula, wherein the watermark extraction formula is as follows:
Wherein w' (x, y) represents the value of the pixel point (x, y) in the layered watermark image, alpha represents the energy value of the third image block, and the coefficient of the first transformation matrix and the coefficient of the second transformation matrix are substituted into the watermark extraction formula to obtain the corresponding pixel value, thereby obtaining the layered watermark image.
And step 10, carrying out inverse scrambling on each layered watermark image to obtain a corresponding layered inverse scrambling image, and fusing all the layered inverse scrambling images to obtain a watermark extraction image.
Specifically, performing Arnold inverse transformation on the layered watermark image to realize inverse scrambling of the layered watermark image, obtaining a corresponding layered anti-scrambling image, if performing continuous Arnold transformation on the color watermark image for M times, performing Arnold inverse transformation on the layered watermark image for M times, and then fusing all the layered anti-scrambling images to obtain a watermark extraction image to realize watermark extraction.
In order to verify the imperceptibility of the color image digital watermarking method in the embodiment of the invention to the image embedded watermark, the invention analyzes the experimental result, and the experiment uses Peak Signal-to-Noise Ratio (PSNR) for measurement. Meanwhile, in order to calculate the similarity between the extracted watermark and the original watermark, normalized correlation (Normalized Correlation, NC) coefficients are adopted.
The color carrier image used in this experiment was an image of 512 x 512 in size. As shown in fig. 2 and 3 (Lena image and Peppers image). The original watermark image is an image of 64 x 64 in size, as shown in fig. 4.
(1) Transparency test
The color image digital watermarking method provided in this embodiment is applied to the sample of fig. 1, so as to obtain a watermarked image Lena (shown in fig. 5) and an extracted watermark image (shown in fig. 6). The color image digital watermarking method provided in this embodiment is applied to the sample of fig. 2, so as to obtain a watermarked image Peppers (shown in fig. 7) and an extracted watermark image (shown in fig. 8).
From the results of fig. 5 and 7, it can be seen that the presence of the watermark is hardly perceived by two images containing the watermark. As can be seen from a comparison of fig. 6, 8 with fig. 4, the original watermark is very similar to the extracted watermark. The PSNR and NC corresponding to the color image digital watermarking method in fig. 2 and 5 are calculated, and the values thereof are psnr=47.013 and nc=1 corresponding to the Lena image, respectively. The PSNR corresponding to the color image digital watermarking method in fig. 3 and 7 was calculated to be psnr=46.514 and nc= 0.9996 corresponding to the NC, peppers image.
(2) Robustness testing
For the robustness of the color image digital watermarking method in the embodiment of the invention, various different attack experiments of doubling the image with 2 color images with watermark, adding salt and pepper noise (coefficient is 0.001), gaussian filtering (coefficient is 0.0005), shearing 1/4, 80% JPEG compression and rotating by 10 degrees are respectively carried out. The watermark extracted after the attack is shown in fig. 9 and 10, respectively.
Meanwhile, the same attack experiment is carried out by using a color image digital watermarking technology based on discrete quaternion cosine transform and discrete octave cosine transform. The comparison was made by calculating the PSNR and NC values of the three methods, respectively, and the comparison results are shown in table 1 below.
Table 1 comparison of PSNR and NC values for three methods under different attacks
As can be seen from the data in table 1 of the above experiment, compared with the color image digital watermarking method based on discrete octant cosine transform and discrete quaternion cosine transform, the color image digital watermarking method provided by the embodiment of the invention has better invisibility and robustness to scaling, noise, filtering, shearing, compression and rotation.
The color image digital watermarking method of the invention utilizes Arnold transformation to scramble R, G, B, H, I, S, L, U, V nine components of the color watermark image respectively, thereby improving the security of watermarking, then integrally carries out discrete cosine transformation based on Clifford algebra on R, G, B, H, I, S, L, U, V nine components of the color carrier image, has high operation efficiency, has better invisibility and robustness compared with the color image digital watermarking method based on discrete eight-element cosine transformation and discrete quaternion cosine transformation, embeds layered scrambled images into each intermediate frequency coefficient of the color carrier image, and finally obtains the color image containing watermarking by means of a preset cosine inverse transformation formula.
As shown in fig. 11, an embodiment of the present invention further provides a color image digital watermarking system, including:
an image acquisition module 10 for acquiring a color watermark image and a color carrier image to be watermarked;
a first representation module 20, configured to obtain a layered carrier image of the corresponding Clifford algebraic representation by using gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel of the Clifford algebraic representation color carrier image;
the watermark scrambling module 30 is configured to scramble R, G, B, H, S, I, L, U, V nine components corresponding to each pixel point of the color watermark image to obtain a corresponding layered scrambled image;
a first transformation module 40, configured to divide each layered carrier image into a plurality of first image blocks, and transform each first image block by using a preset cosine transform formula to obtain a corresponding first transformation matrix;
the watermark embedding module 50 is configured to embed each pixel point on each layered scrambled image into an intermediate frequency coefficient in a corresponding first transformation matrix, so as to obtain a corresponding embedding matrix;
and the inverse transformation module 60 is configured to inverse transform each of the embedded matrices by using a preset cosine inverse transformation formula, obtain corresponding second image blocks embedded with the watermark, and combine all the second image blocks to obtain the color image added with the watermark.
Further, the color image digital watermarking system further includes:
a second algebraic representation module 70, configured to obtain a layered color image of the corresponding Clifford algebraic representation by using the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel of the watermarked color image of the Clifford algebraic representation;
a second transformation module 80, configured to divide each layered color image into a plurality of third image blocks, and transform each third image block by using the preset cosine transform formula to obtain a corresponding second transformation matrix;
a watermark extraction module 90, configured to extract a corresponding layered watermark image by using the second transformation matrix and the corresponding first transformation matrix in each of the layered color images;
the watermark anti-scrambling module 100 carries out anti-scrambling on each layered watermark image to obtain a corresponding layered anti-scrambling image, and fuses all the layered anti-scrambling images to obtain a watermark extraction image.
The specific configuration of the color image digital watermarking system can be referred to above for the configuration of the color image digital watermarking method, and will not be described herein. The various modules of the color image digital watermarking system described above may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 12. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a color image digital watermarking method.
It will be appreciated by those skilled in the art that the structure shown in fig. 12 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory storing a computer program and a processor that when executing the computer program performs the steps of:
acquiring a color watermark image and a color carrier image to be watermarked;
obtaining a layered carrier image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the Clifford algebraic representation color carrier image;
scrambling R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color watermark image to obtain a corresponding layered scrambling image;
dividing each layered carrier image into a plurality of first image blocks, and transforming each first image block by using a preset cosine transform formula to obtain a corresponding first transformation matrix;
respectively embedding each pixel point on each layered scrambling image into an intermediate frequency coefficient in a corresponding first transformation matrix to obtain a corresponding embedding matrix;
and carrying out inverse transformation on each embedded matrix by using a preset cosine inverse transformation formula to obtain corresponding second image blocks embedded with the watermark, and combining all the second image blocks to obtain the color image added with the watermark.
In one embodiment, further comprising:
obtaining a layered color image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color image after the watermark is added by the Clifford algebraic representation;
dividing each layered color image into a plurality of third image blocks, and transforming each third image block by using the preset cosine transform formula to obtain a corresponding second transformation matrix;
extracting a corresponding layered watermark image by using a second transformation matrix and a corresponding first transformation matrix in each layered color image;
and carrying out inverse scrambling on each layered watermark image to obtain a corresponding layered inverse scrambling image, and fusing all the layered inverse scrambling images to obtain a watermark extraction image.
In one embodiment, said extracting the corresponding layered watermark image using the second transformation matrix and the corresponding first transformation matrix in each of said layered color images comprises:
calculating each layered watermark image by adopting a watermark extraction formula, wherein the watermark extraction formula is as follows:
wherein w' (x, y) represents the value of the pixel (x, y) in the layered watermark image, alpha represents the energy value of the third image block, Coefficients representing the midpoints (p, s) of the second transformation matrix,/and>coefficients representing points (p, s) in the first transformation matrix.
In one embodiment, the preset cosine transform formula is:
/>
where u is a unit Clifford algebra, modulo 1, and u 2 Is-1, f (X, Y) represents the value of the pixel point (X, Y) on the image by Clifford algebra to be subjected to cosine transform, X represents the number of pixels in the image row, Y represents the number of pixels in the image column, p represents the position of the midpoint (p, s) of the matrix in the row direction, s represents the position of the midpoint (p, s) of the matrix in the column direction, C (e) (p, s) represents coefficients of points (p, s) of the transform matrix obtained after the cosine transform;
transforming each first image block by using a preset cosine transform formula to obtain a corresponding first transformation matrix, including:
substituting each first image block serving as a Clifford algebraic representation image to be subjected to cosine transform into the preset cosine transform formula, and then calculating to obtain a corresponding first transformation matrix.
In one embodiment, the embedding each pixel point on each hierarchically scrambled image into the intermediate frequency coefficient in the corresponding first transformation matrix to obtain the corresponding embedding matrix includes:
Embedding each pixel point on each layered scrambling image into an intermediate frequency coefficient in a corresponding first transformation matrix by using an embedding formula to obtain a corresponding embedding coefficient, wherein the embedding formula is as follows:
wherein alpha is i Representing the energy value of the hierarchically scrambled image, w (x, y) represents the number of pixels (x,the value of y) is set to be equal to,intermediate frequency coefficients representing the first transformation matrix, +.>Coefficients representing the embedding matrix;
and forming a corresponding embedding matrix according to the embedding coefficients corresponding to each layered scrambling image.
In one embodiment, the preset inverse cosine transform formula is:
/>
where u is a unit Clifford algebra, modulo 1, and u 2 For-1, c (p, s) denotes the coefficient of the midpoint (p, s) of the embedded matrix to be subjected to the inverse cosine transform, X denotes the number of points in the row direction of the matrix, Y denotes the number of points in the column direction of the matrix, p denotes the position of the midpoint (p, s) in the row direction of the matrix, s denotes the position of the midpoint (p, s) in the column direction of the matrix, and f' (X, Y) denotes the value of the pixel point (X, Y) in the second image block obtained after the inverse cosine transform.
Performing inverse transformation on each embedded matrix by using a preset cosine inverse transformation formula to obtain a corresponding second image block embedded with the watermark, wherein the method comprises the following steps:
Substituting each embedded matrix into the preset cosine transform formula, and then calculating to obtain a corresponding second image block with the embedded watermark.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring a color watermark image and a color carrier image to be watermarked;
obtaining a layered carrier image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the Clifford algebraic representation color carrier image;
scrambling R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color watermark image to obtain a corresponding layered scrambling image;
dividing each layered carrier image into a plurality of first image blocks, and transforming each first image block by using a preset cosine transform formula to obtain a corresponding first transformation matrix;
respectively embedding each pixel point on each layered scrambling image into an intermediate frequency coefficient in a corresponding first transformation matrix to obtain a corresponding embedding matrix;
and carrying out inverse transformation on each embedded matrix by using a preset cosine inverse transformation formula to obtain corresponding second image blocks embedded with the watermark, and combining all the second image blocks to obtain the color image added with the watermark.
In one embodiment, further comprising:
obtaining a layered color image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color image after the watermark is added by the Clifford algebraic representation;
dividing each layered color image into a plurality of third image blocks, and transforming each third image block by using the preset cosine transform formula to obtain a corresponding second transformation matrix;
extracting a corresponding layered watermark image by using a second transformation matrix and a corresponding first transformation matrix in each layered color image;
and carrying out inverse scrambling on each layered watermark image to obtain a corresponding layered inverse scrambling image, and fusing all the layered inverse scrambling images to obtain a watermark extraction image.
In one embodiment, said extracting the corresponding layered watermark image using the second transformation matrix and the corresponding first transformation matrix in each of said layered color images comprises:
calculating each layered watermark image by adopting a watermark extraction formula, wherein the watermark extraction formula is as follows:
wherein w' (x, y) represents the value of the pixel (x, y) in the layered watermark image, alpha represents the energy value of the third image block, Coefficients representing the midpoints (p, s) of the second transformation matrix,/and>coefficients representing points (p, s) in the first transformation matrix.
In one embodiment, the preset cosine transform formula is:
where u is a unit Clifford algebra, modulo 1, and u 2 Is-1, f (X, Y) represents the value of the pixel point (X, Y) on the image by Clifford algebra to be subjected to cosine transform, X represents the number of pixels in the image row, Y represents the number of pixels in the image column, p represents the position of the midpoint (p, s) of the matrix in the row direction, s represents the position of the midpoint (p, s) of the matrix in the column direction, C (e) (p, s) represents coefficients of points (p, s) of the transform matrix obtained after the cosine transform;
transforming each first image block by using a preset cosine transform formula to obtain a corresponding first transformation matrix, including:
substituting each first image block serving as a Clifford algebraic representation image to be subjected to cosine transform into the preset cosine transform formula, and then calculating to obtain a corresponding first transformation matrix.
In one embodiment, the embedding each pixel point on each hierarchically scrambled image into the intermediate frequency coefficient in the corresponding first transformation matrix to obtain the corresponding embedding matrix includes:
Embedding each pixel point on each layered scrambling image into an intermediate frequency coefficient in a corresponding first transformation matrix by using an embedding formula to obtain a corresponding embedding coefficient, wherein the embedding formula is as follows:
wherein alpha is i Representing the energy value of the hierarchically scrambled image, w (x, y) representing the value of the pixel (x, y) in the hierarchically scrambled image,intermediate frequency coefficients representing the first transformation matrix, +.>Representation inlayCoefficients into the matrix;
and forming a corresponding embedding matrix according to the embedding coefficients corresponding to each layered scrambling image.
In one embodiment, the preset inverse cosine transform formula is:
/>
where u is a unit Clifford algebra, modulo 1, and u 2 For-1, c (p, s) denotes the coefficient of the midpoint (p, s) of the embedded matrix to be subjected to the inverse cosine transform, X denotes the number of points in the row direction of the matrix, Y denotes the number of points in the column direction of the matrix, p denotes the position of the midpoint (p, s) in the row direction of the matrix, s denotes the position of the midpoint (p, s) in the column direction of the matrix, and f (X, Y) denotes the value of the pixel point (X, Y) in the second image block obtained after the inverse cosine transform.
Performing inverse transformation on each embedded matrix by using a preset cosine inverse transformation formula to obtain a corresponding second image block embedded with the watermark, wherein the method comprises the following steps:
Substituting each embedded matrix into the preset cosine transform formula, and then calculating to obtain a corresponding second image block with the embedded watermark.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
Claims (10)
1. A color image digital watermarking method, comprising:
acquiring a color watermark image and a color carrier image to be watermarked;
obtaining a layered carrier image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the Clifford algebraic representation color carrier image;
scrambling R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color watermark image to obtain a corresponding layered scrambling image;
dividing each layered carrier image into a plurality of first image blocks, and transforming each first image block by using a preset cosine transform formula to obtain a corresponding first transformation matrix;
respectively embedding each pixel point on each layered scrambling image into an intermediate frequency coefficient in a corresponding first transformation matrix to obtain a corresponding embedding matrix;
And carrying out inverse transformation on each embedded matrix by using a preset cosine inverse transformation formula to obtain corresponding second image blocks embedded with the watermark, and combining all the second image blocks to obtain the color image added with the watermark.
2. The color image digital watermarking method of claim 1, further comprising:
obtaining a layered color image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color image after the watermark is added by the Clifford algebraic representation;
dividing each layered color image into a plurality of third image blocks, and transforming each third image block by using the preset cosine transform formula to obtain a corresponding second transformation matrix;
extracting a corresponding layered watermark image by using a second transformation matrix and a corresponding first transformation matrix in each layered color image;
and carrying out inverse scrambling on each layered watermark image to obtain a corresponding layered inverse scrambling image, and fusing all the layered inverse scrambling images to obtain a watermark extraction image.
3. The color image digital watermarking method according to claim 2, wherein extracting the corresponding layered watermark image using the second transformation matrix and the corresponding first transformation matrix in each of the layered color images includes:
Calculating each layered watermark image by adopting a watermark extraction formula, wherein the watermark extraction formula is as follows:
wherein w' (x, y) represents the value of the pixel (x, y) in the layered watermark image, alpha represents the energy value of the third image block,coefficients representing the midpoints (p, s) of the second transformation matrix,/and>coefficients representing points (p, s) in the first transformation matrix.
4. The color image digital watermarking method according to claim 1, wherein the predetermined cosine transform formula is:
where u is a unit Clifford algebra, modulo 1, and u 2 Is-1, f (X, Y) represents the value of the pixel point (X, Y) on the image by Clifford algebra to be subjected to cosine transform, X represents the number of pixels in the image row, Y represents the number of pixels in the image column, p represents the position of the midpoint (p, s) of the matrix in the row direction, s represents the position of the midpoint (p, s) of the matrix in the column direction, C (e) (p, s) represents coefficients of points (p, s) of the transform matrix obtained after the cosine transform;
transforming each first image block by using a preset cosine transform formula to obtain a corresponding first transformation matrix, including:
substituting each first image block serving as a Clifford algebraic representation image to be subjected to cosine transform into the preset cosine transform formula, and then calculating to obtain a corresponding first transformation matrix.
5. The method of digital watermarking a color image according to claim 1, wherein the step of embedding each pixel point on each hierarchically scrambled image into an intermediate frequency coefficient in a corresponding first transformation matrix to obtain a corresponding embedding matrix includes:
embedding each pixel point on each layered scrambling image into an intermediate frequency coefficient in a corresponding first transformation matrix by using an embedding formula to obtain a corresponding embedding coefficient, wherein the embedding formula is as follows:
wherein alpha is i Representing the energy value of the hierarchically scrambled image, w (x, y) representing the value of the pixel (x, y) in the hierarchically scrambled image,intermediate frequency coefficients representing the first transformation matrix, +.>Coefficients representing the embedding matrix;
and forming a corresponding embedding matrix according to the embedding coefficients corresponding to each layered scrambling image.
6. The color image digital watermarking method according to claim 1, wherein the preset inverse cosine transform formula is:
where u is a unit Clifford algebra, modulo 1, and u 2 For-1, c (p, s) denotes the coefficient of the midpoint (p, s) of the embedded matrix to be subjected to the inverse cosine transform, X denotes the number of points in the row direction of the matrix, Y denotes the number of points in the column direction of the matrix, p denotes the position of the midpoint (p, s) in the row direction of the matrix, s denotes the position of the midpoint (p, s) in the column direction of the matrix, and f' (X, Y) denotes the value of the pixel point (X, Y) in the second image block obtained after the inverse cosine transform.
Performing inverse transformation on each embedded matrix by using a preset cosine inverse transformation formula to obtain a corresponding second image block embedded with the watermark, wherein the method comprises the following steps:
substituting each embedded matrix into the preset cosine transform formula, and then calculating to obtain a corresponding second image block with the embedded watermark.
7. A color image digital watermarking system, comprising:
the image acquisition module is used for acquiring a color watermark image and a color carrier image to be watermarked;
the first-coefficient representation module is used for obtaining a layered carrier image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the Clifford algebraic representation color carrier image;
the watermark scrambling module is used for scrambling R, G, B, H, S, I, L, U, V nine components corresponding to each pixel point of the color watermark image to obtain a corresponding layered scrambling image;
the first transformation module is used for dividing each layered carrier image into a plurality of first image blocks, and transforming each first image block by using a preset cosine transformation formula to obtain a corresponding first transformation matrix;
The watermark embedding module is used for respectively embedding each pixel point on each layered scrambling image into the intermediate frequency coefficient in the corresponding first transformation matrix to obtain a corresponding embedding matrix;
and the inverse transformation module is used for carrying out inverse transformation on each embedded matrix by utilizing a preset cosine inverse transformation formula to obtain corresponding second image blocks embedded with the watermark, and combining all the second image blocks to obtain the color image added with the watermark.
8. The color image digital watermarking system of claim 1, further comprising:
the second algebraic representation module is used for obtaining a layered color image of the corresponding Clifford algebraic representation by utilizing the gray values of R, G, B, H, S, I, L, U, V components corresponding to each pixel point of the color image after the watermark is added by the Clifford algebraic representation;
the second transformation module is used for dividing each layered color image into a plurality of third image blocks, and transforming each third image block by utilizing the preset cosine transformation formula to obtain a corresponding second transformation matrix;
the watermark extraction module is used for extracting a corresponding layered watermark image by utilizing the second transformation matrix and the corresponding first transformation matrix in each layered color image;
And the watermark anti-scrambling module carries out anti-scrambling on each layered watermark image to obtain a corresponding layered anti-scrambling image, and fuses all the layered anti-scrambling images to obtain a watermark extraction image.
9. Computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1-6 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1-6.
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| 吴明珠等: "基于离散八元数余弦变换的彩色图像水印算法", 《计算机应用于软件》, 31 July 2016 (2016-07-31), pages 1 - 5 * |
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