CN119515653A - Digital Watermarking Algorithm in YUV Domain Based on Wavelet Transform - Google Patents
Digital Watermarking Algorithm in YUV Domain Based on Wavelet Transform Download PDFInfo
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Abstract
The invention provides a YUV domain digital watermarking algorithm based on wavelet transformation, which comprises the steps of separating an original image to obtain an embedded channel, carrying out two-stage wavelet transformation on the embedded channel, calculating a low-frequency band pixel average value LL in a second-stage low-frequency sub-band, obtaining the watermark intensity embedded by the embedded channel according to the corresponding relation between the LL and the watermark intensity amplitude, embedding the watermark into a first-stage high-frequency sub-band to obtain a watermark-carrying second-stage high-frequency sub-band, carrying out wavelet inverse transformation to obtain a watermark-carrying channel, and merging the channels to obtain a watermark-carrying image. By adopting two-stage wavelet transformation, only 2 lines of buffer areas and addition and subtraction shift operation are needed, and the cost is low. Aiming at the visual characteristics of YUV three channels, different intensity curves are designed for the YUV three channels, and the watermark is embedded in any channel in YUV to obtain better image quality. The load is high, and longer information can be hidden. The robustness is high, and the high accuracy is still achieved under the strong noise transmission channel.
Description
Technical Field
The invention belongs to the technical field of integrated circuit manufacturing, and particularly relates to a YUV domain digital watermarking algorithm based on wavelet transformation.
Background
The development of digital technology and networking has enabled digital information to be conveniently and rapidly spread over the network, however, while a fast and accurate means of digital transmission has provided convenience to people, new challenges are presented, such as infringement, piracy and random tampering of digital products. The digital watermarking technology is a new direction in the technical field of information security at present, is a novel technology capable of protecting copyright, authentication sources and integrity under an open network environment, and has very wide application prospects in the aspects of tamper identification, hierarchical access of data, data tracking and detection, business and video broadcasting, service payment of network digital media, electronic commerce authentication and identification and the like. The wavelet transformation known as a 'mathematical microscope' has good time-frequency characteristics and consistency with a human eye vision system, and after wavelet inverse transformation, the added watermark information is basically and uniformly dispersed on the whole image, so that noise and filtering to a certain extent cannot interfere with hidden information, and the robustness to shearing, noise and filtering can be greatly improved.
YUV is a low bandwidth color coding model, widely used in image transmission. According to different sampling modes, YUV derives different formats to cope with different bandwidth requirements. Compared with the traditional RAW domain or RGB domain, the YUV domain watermark is not subjected to image post-processing, is only affected by a transmission channel, and is a more reliable carrier. However, the traditional watermark algorithm is only embedded into a specific channel, the watermark load is low, the quality of the watermark image is low, the channel characteristics of Y, U and V three channels are not considered, and the channel characteristics are not optimized.
Disclosure of Invention
The invention aims to provide a YUV domain digital watermarking algorithm based on wavelet transformation, which adopts two-stage wavelet transformation, only needs 2 lines of buffer areas and addition and subtraction shift operation, and has lower cost. Aiming at YUV visual characteristics, YUV three channels are designed with different intensity curves, and watermark embedding in any channel in YUV can obtain better watermark image quality. The load is high, longer information can be hidden, and the Y channel has twice the hiding capacity of the U/V channel, so that the higher load requirement can be met. The robustness is high, and the high accuracy is still achieved under the strong noise transmission channel.
The invention provides a YUV domain digital watermarking algorithm based on wavelet transformation, comprising the following steps:
s1, separating an original image to obtain an embedded channel, wherein the embedded channel is any one channel of YUV three channels obtained by separating the original image;
S2, carrying out primary haar wavelet transformation on the embedded channel to obtain four primary sub-bands, wherein the four primary sub-bands sequentially comprise a primary low-frequency sub-band, a primary middle-high frequency sub-band in the vertical direction, a primary middle-high frequency sub-band in the horizontal direction and a primary high frequency sub-band;
s3, performing secondary haar wavelet transformation on the primary high-frequency sub-band to obtain four first secondary sub-bands, wherein the four first secondary sub-bands comprise first secondary high-frequency sub-bands;
s4, performing secondary haar wavelet transformation on the primary low-frequency sub-band to obtain four secondary sub-bands, wherein the four secondary sub-bands comprise secondary low-frequency sub-bands;
S5, calculating a low-frequency band pixel average value LL in the second-level low-frequency sub-band, and obtaining the watermark intensity alpha of the embedded channel embedded with the watermark according to the corresponding relation between the low-frequency band pixel average value LL and the watermark intensity amplitude Z;
S6, embedding the watermark into the first second-level high-frequency sub-band according to the calculated watermark strength, so as to obtain a watermark-carrying second-level high-frequency sub-band;
S7, carrying out wavelet inverse transformation on all sub-bands containing the watermark-carrying second-level high-frequency sub-band to obtain a watermark-carrying channel, and combining the watermark-carrying channel and the non-watermark-carrying channel to obtain a watermark-carrying image.
Further, the step S2 specifically includes performing 2-dimensional haar wavelet transform on the embedded channel by using a2×2 pixel block as a unit, where A0, A1, A2, and A3 are pixel values of 4 pixels of the 2×2 pixel block, L0, L1, L2, and L3 are coefficients of the four first-level subbands sequentially corresponding to each other, and the calculation method is as follows:
L0=A0+A1+A2+A3;L1=A0+A1-A2-A3;
L2=A0-A1+A2-A3;L3=A0-A1-A2+A3。
Further, the step S3 specifically includes performing 1-dimensional haar wavelet transform on the primary high-frequency sub-band by taking 1*4 pixel blocks as units, wherein the four first secondary sub-bands are sequentially a first secondary low-frequency sub-band, a first secondary vertical middle-high-frequency sub-band, a first secondary horizontal middle-high-frequency sub-band and the first secondary high-frequency sub-band, B0, B1, B2 and B3 are respectively pixel values of 4 pixels of 1*4 pixel blocks in the primary high-frequency sub-band, L30, L31, L32 and L33 are respectively coefficients sequentially corresponding to the four first secondary sub-bands, and the calculation mode is as follows:
L30=B0+B1+B2+B3;L31=B0+B1-B2-B3;
L32=B0-B1+B2-B3;L33=B0-B1-B2+B3。
further, the step S4 specifically includes performing 1-dimensional haar wavelet transform on the first-level low-frequency sub-band by taking 1*4 pixel blocks as units, wherein the four second-level sub-bands are sequentially the second-level low-frequency sub-band, the second-level vertical mid-high-frequency sub-band, the second-level horizontal mid-high-frequency sub-band and the second-level high-frequency sub-band, C0, C1, C2 and C3 are respectively pixel values of 4 pixels of 1*4 pixel blocks in the first-level low-frequency sub-band, L00, L01, L02 and L03 are respectively corresponding coefficients of the four second-level sub-bands in sequence, and the calculation mode is as follows:
L00=C0+C1+C2+C3;L01=C0+C1-C2-C3;
L02=C0-C1+C2-C3;L03=C0-C1-C2+C3。
Further, the first-stage low-frequency sub-band is m rows by 4n columns of pixels, the second-stage low-frequency sub-band obtained by the haar wavelet transformation is m rows by n columns of coefficient matrixes, L00 represents any one coefficient in the coefficient matrixes, and the actually calculated low-frequency pixel average value LL=L00/16.
Further, the step S5 specifically includes:
Obtaining k+1 typical values of the low-frequency band pixel average value from small to large intervals according to experiments or experience, and correspondingly dividing k sections or segments;
obtaining the watermark intensity amplitude values of the k+1Y channels embedded watermark, wherein the k+1 typical values are in one-to-one correspondence;
Obtaining the watermark intensity amplitude values of the k+1U channels and the V channels which are in one-to-one correspondence with the k+1 typical values, wherein the watermark intensity amplitude values of the U channels and the V channels which are in one-to-one correspondence with the same typical value are equal, and the watermark intensity amplitude values of the Y channels which are in one-to-one correspondence with the same typical value are smaller than the watermark intensity amplitude values of the U channels or the V channels.
Further, in step S5, the watermark strength magnitude Z is calculated according to the following formula,
Wherein x 0-xk represents k+1 of said typical values, when calculating said Y channel, said Y 0-yk represents k+1 of said Y channel watermark intensity magnitudes, when calculating said U channel and said V channel, said Y 0-yk represents k+1 of said U channel and said V channel watermark intensity magnitudes, n is any integer number between 1 and k;
When the calculated average value LL < x k of the low-frequency band pixels of x 0 < x, according to the size of the LL value, using interpolation method to calculate, inserting LL into a corresponding one of the sections (x n-1,xn), determining a straight line by two points (x n-1,yn-1) and (x n,yn), using LL as the horizontal coordinate corresponding to the straight line, and calculating the vertical coordinate of the LL point corresponding to the straight line as the watermark intensity amplitude Z.
Further, in step S5, setting the maximum variation of the pixel value of the pixel in the time domain caused by the embedding of the watermark in the pixel in the embedded channel as Δp, calculating the corresponding maximum watermark intensity value Δn=Δp×16 in the frequency domain, and calculating the watermark intensity value alpha=z×Δn.
Further, step S6 specifically includes:
Dividing the first secondary frequency sub-band into blocks according to 2 x 2, setting a watermark embedding mode corresponding to each Bit of watermark as P, wherein P comprises a 2 x 2 matrix formed by elements of-1/1 and the sum of all elements is 0;
L33' =l33+p x alpha (if bit=1);
L33' =l33-p×alpha (if bit=0).
Further, step S7 specifically includes:
S71, performing 1-dimensional wavelet inverse transformation, namely performing 1-dimensional haar wavelet inverse transformation on the first secondary low-frequency sub-band, the first secondary middle-high-frequency sub-band in the vertical direction, the first secondary middle-high-frequency sub-band and the watermark-carrying secondary high-frequency sub-band to obtain an inverse transformation primary high-frequency sub-band;
b0', B1', B2', B3' are the pixel values of 4 pixels of 1*4 pixel blocks in the inverse transform first-level high-frequency subband, respectively;
B0’=L30+L31+L32+L33’;B1’=L30+L31-L32-L33’;
B2’=L30-L31+L32-L33’;B3’=L30-L31-L32+L33’。
Further, step S7 specifically further includes:
S72, performing 2-dimensional wavelet inverse transformation, namely performing 2-dimensional haar wavelet inverse transformation on the primary low-frequency sub-band, the primary middle-high frequency sub-band in the vertical direction, the primary middle-high frequency sub-band in the horizontal direction and the inverse transformation primary high-frequency sub-band to obtain the watermark carrying channel;
A0', A1', A2', A3' are respectively the pixel values of 4 pixels of A2 x 2 pixel block in the watermark carrying channel, L3' is the coefficient of the first-stage high-frequency sub-band of the inverse transform, L0 is the coefficient of the first-stage low-frequency sub-band, L1 is the coefficient of the first-stage middle-high-frequency sub-band in the vertical direction, and L2 is the coefficient of the first-stage middle-high-frequency sub-band in the horizontal direction;
A0’=L0+L1+L2+L3';A1’=L0+L1-L2-L3';
A2’=L0-L1+L2-L3';A3’=L0-L1-L2+L3'。
further, the method also comprises watermark extraction, wherein the watermark extraction comprises the following steps:
Separating YUV channels of the watermark-carrying image to obtain the watermark-carrying channel, wherein the watermark-carrying channel is any one channel of a watermark-carrying Y channel, a watermark-carrying U channel and a watermark-carrying V channel;
performing primary wavelet transform, and performing 2-dimensional haar wavelet transform on the watermark-carrying channel by taking 2x 2 pixel blocks as units to obtain 4 primary extraction sub-bands, wherein the 4 primary extraction sub-bands comprise primary extraction high-frequency sub-bands;
performing secondary wavelet transformation, namely performing 1-dimensional haar wavelet transformation on the primary extraction high-frequency sub-band by taking 1*4 pixel blocks as units to obtain 4 secondary extraction sub-bands, wherein the 4 secondary extraction sub-bands comprise secondary extraction high-frequency sub-bands;
Dividing coefficients in the secondary extraction high-frequency sub-band to obtain coefficient matrix blocks, sequentially calculating and extracting watermark Bit values of each coefficient matrix block, splicing all the extracted watermark Bit values Bit to obtain a final watermark, wherein in each coefficient matrix block, if a result of matrix point multiplication operation of the coefficient matrix block and the watermark embedding mode P is greater than 0, bit=1, and if a result of matrix point multiplication operation of the coefficient matrix block and the watermark embedding mode P is less than 0, bit=0.
Compared with the prior art, the invention has the following beneficial effects:
The invention provides a YUV domain digital watermarking algorithm based on wavelet transformation, which comprises S1, separating an original image to obtain an embedded channel, wherein the embedded channel is any one channel of YUV three channels obtained by separating the original image; watermark embedding is only carried out on one channel in the YUV three channels; S2, carrying out primary haar wavelet transformation on the embedded channel to obtain four primary sub-bands, wherein the four primary sub-bands sequentially comprise a primary low-frequency sub-band, a primary middle-high frequency sub-band in the vertical direction, a primary middle-high frequency sub-band and a primary high frequency sub-band, S3, carrying out secondary haar wavelet transformation on the primary high frequency sub-band to obtain four first secondary sub-bands, wherein the four first secondary sub-bands comprise a first secondary sub-band, S4, carrying out secondary haar wavelet transformation on the primary low frequency sub-band to obtain four second secondary sub-bands, the four second secondary sub-bands comprise a second secondary low frequency sub-band, S5, calculating the average value LL of low frequency pixels in the second secondary low frequency sub-band, obtaining the watermark intensity of the watermark embedded channel according to the corresponding relation between the average value LL of the low frequency pixels and the watermark intensity amplitude Z, S6, carrying out inverse transformation on the first secondary sub-band and the second secondary sub-band according to the calculated intensity, and carrying out watermark-embedding on the primary low frequency sub-band to obtain the watermark carrier image, and carrying the watermark carrier image which is not carrying 7, and carrying out watermark-carrying on the two-level watermark-carrying sub-band.
The invention adopts two-stage wavelet transformation, only needs 2 lines of buffer areas and addition and subtraction shift operation, and has lower cost. Aiming at YUV visual characteristics, YUV three channels are designed with different intensity curves, and watermark embedding in any channel in YUV can obtain better image quality. The load is high, longer information can be hidden, and the Y channel has twice the hiding capacity of the U/V channel, so that the higher load requirement can be met. The robustness is high, and the high accuracy is still achieved under the strong noise transmission channel.
Drawings
Fig. 1 is a schematic flow chart of a YUV domain digital watermarking algorithm based on wavelet transform according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of a first order wavelet transform performed in the algorithm of the present invention.
Fig. 3 is a schematic diagram of the two-level wavelet transform of the first-level high-frequency subband HH1 in the algorithm of the present invention.
Fig. 4 is a schematic diagram of performing a two-level wavelet transform on a first-level low-frequency subband LL1 in the algorithm of the present invention.
Fig. 5 is a table of watermark strength in the algorithm of the present invention.
Fig. 6 is a plot of watermark intensity magnitude Z versus low-band pixel average LL in the algorithm of the present invention.
Fig. 7 is a schematic diagram of embedding a watermark into a first secondary high frequency sub-band HH2a to obtain a watermarked secondary high frequency sub-band HH2a' in the algorithm of the present invention.
Fig. 8 is a schematic diagram of an inverse 1-dimensional wavelet transform in the algorithm of the present invention.
Fig. 9 is a schematic diagram of an inverse 2-dimensional wavelet transform in accordance with the algorithm of the present invention.
Fig. 10 is a schematic diagram of the primary wavelet transform performed by the watermark carrying channel C' in the algorithm of the present invention.
Fig. 11 is a schematic diagram of the first-order extraction of the high-frequency subband HH1t for the second-order wavelet transform in the algorithm of the present invention.
Fig. 12 is a schematic diagram of watermark extraction accuracy under a lossless transmission channel.
Fig. 13 is a schematic diagram of watermark extraction accuracy under strong noise channel transmission.
Fig. 14 is a first diagram of image quality for an original image, a watermark Y-channel, a watermark U-channel, and a watermark V-channel.
Fig. 15 is a second schematic diagram of image quality of an original image, a watermark Y-channel, a watermark U-channel, and a watermark V-channel.
Detailed Description
The invention is described in further detail below with reference to the drawings and the specific examples. The advantages and features of the present invention will become more apparent from the following description. It should be noted that the drawings are in a very simplified form and are not to scale precisely, but rather merely for the purpose of facilitating and clearly aiding in the description of the embodiments of the invention.
For ease of description, some embodiments of the application may use spatially relative terms, such as "above," "below," "top," "below," and the like, to describe one element or component's relationship to another element(s) or component(s) as illustrated in the figures of the embodiments. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is turned over, elements or components described as "below" or "beneath" other elements or components would then be oriented "above" or "over" the other elements or components. The terms "first," "second," and the like, herein below, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that such terms so used are interchangeable under appropriate circumstances.
The embodiment of the invention provides a YUV domain digital watermarking algorithm based on wavelet transformation, which comprises the following steps as shown in figure 1:
S1, separating an original image to obtain an embedded channel, wherein the embedded channel is any one channel of YUV three channels obtained by separating the original image;
S2, carrying out primary haar wavelet transformation on the embedded channel to obtain four primary sub-bands, wherein the four primary sub-bands sequentially comprise a primary low-frequency sub-band, a primary vertical middle-high frequency sub-band, a primary horizontal middle-high frequency sub-band and a primary high frequency sub-band;
S3, performing secondary haar wavelet transformation on the primary high-frequency sub-band to obtain four first secondary sub-bands, wherein the four first secondary sub-bands comprise first secondary high-frequency sub-bands;
S4, performing secondary haar wavelet transformation on the primary low-frequency sub-band to obtain four secondary sub-bands, wherein the four secondary sub-bands comprise secondary low-frequency sub-bands;
S5, calculating a low-frequency band pixel average value LL in a second-level low-frequency sub-band, and obtaining the watermark intensity alpha of the embedded channel embedded with the watermark according to the corresponding relation between the low-frequency band pixel average value LL and the watermark intensity amplitude Z;
S6, embedding the watermark into the first second-level high-frequency sub-band according to the calculated watermark intensity, so as to obtain a watermark-carrying second-level high-frequency sub-band;
S7, carrying out wavelet inverse transformation on all sub-bands containing the watermark-carrying second-level high-frequency sub-band to obtain a watermark-carrying channel, and combining the watermark-carrying channel and the non-watermark-carrying channel to obtain a watermark-carrying image.
The following describes in detail each step of the YUV domain digital watermarking algorithm based on wavelet transform according to the embodiment of the present invention with reference to the accompanying drawings.
S1, separating an original image to obtain an embedded channel C, wherein the embedded channel C is any one channel of YUV three channels obtained by separating the original image, and watermark embedding is only embedded into one channel of the YUV three channels. In the whole watermark embedding operation, only one channel of YUV three channels is embedded, and if any two channels or three channels are embedded with watermarks, the image quality is affected.
The original image may be in RAW format or RGB format. The image may be represented using different color spaces, of which RGB (red green blue) and YUV (luminance-chrominance) color spaces are common, and the RGB color space is one of the most common color representation modes, in which the color of the image is composed of intensities of three channels of red (R), green (G) and blue (B). The value of each channel is typically in the range of 0 to 255, representing the brightness of the color channel. The YUV color space is a color space for representing brightness and chromaticity of an image, a brightness channel (Y) represents brightness of the image, and chromaticity channels (U and V) represent differences in color. Since the human eye is more sensitive to luminance variations and relatively less sensitive to chrominance variations, extracting features of an image can be more conveniently performed by converting the image into YUV format, with luminance (Y) and chrominance (U, V) components being explicitly separated.
Converting the RGB format of an original image into a YUV format according to a calculation formula, and separating a Y channel, a U channel and a V channel, wherein the formula is as follows:
Y=0.299×R+0.587×G+0.114×B;
U=0.564×(B-Y);V=0.713×(R-Y)。
Wherein Y represents a luminance channel, U and V each represent a chrominance channel, R, G, B are red, green and blue of the image, respectively. By the operation of the formula, YUV three channels can be obtained. The invention is based on a mathematical model, the Y component occupies the most weight in the final mapping to the RGB domain, and the U/V component occupies the approximate weight. Based on a physical model, the human eye is more sensitive to the brightness Y component, and the chromaticity U/V component does not obviously influence the visual effect.
Step S2, as shown in FIG. 2, performing primary wavelet transform, and performing primary haar wavelet transform on the embedded channel C to obtain four primary sub-bands, wherein the four primary sub-bands sequentially comprise a primary low-frequency sub-band LL1, a primary vertical middle-high frequency sub-band HL1, a primary horizontal middle-high frequency sub-band LH1 and a primary high-frequency sub-band HH1. The wavelet transform can decompose the image in multiple resolutions, and each level of wavelet transform obtains 4 subbands, namely a low-frequency subband LL, a high-frequency subband HL in the vertical direction, a high-frequency subband LH in the horizontal direction and a high-frequency subband HH. Haar wavelet transform is a signal processing method based on wavelet analysis that can decompose a signal into a plurality of sub-signals of different frequencies.
Specifically, the embedded channel C performs 2-dimensional haar wavelet transform with a2×2 pixel block as a unit to obtain 4 primary subbands. For example, the embedded channel C is a matrix of pixels of, for example, 64×64 (64 rows by 64 columns), resulting in a coefficient matrix of 32×32 for each of the 4 primary subbands. The calculation method is as follows:
A0, A1, A2, A3 are respectively the pixel values of 4 pixels of A2 x2 pixel block embedded in the channel C, L0 is a coefficient of the primary low-frequency sub-band LL1, L0 can be understood as an output value (also called a coefficient) of the primary low-frequency sub-band LL1 obtained by carrying out 2-dimensional haar primary wavelet transform on the embedded channel C, and all the coefficients form the primary low-frequency sub-band LL 1. L1 is the coefficient of the high-frequency subband HL1 in the primary vertical direction, L2 is the coefficient of the high-frequency subband LH1 in the primary horizontal direction, and L3 is the coefficient of the primary high-frequency subband HH 1.
L0=A0+A1+A2+A3;L1=A0+A1-A2-A3;
L2=A0-A1+A2-A3;L3=A0-A1-A2+A3。
Step S3, as shown in FIG. 3, performing two-level wavelet transform, and performing 1-dimensional haar wavelet transform on the first-level high-frequency sub-band HH1 by taking 1*4 pixel blocks as units to obtain 4 first-level sub-bands, namely a first-level low-frequency sub-band LL2a, a first-level vertical middle-high-frequency sub-band HL2a, a first-level horizontal middle-high-frequency sub-band LH2a and a first-level high-frequency sub-band HH2a. The calculation method is as follows:
b0, B1, B2, B3 are pixel values of 4 pixels of 1*4 pixel blocks in the first-level high-frequency subband HH1, L30 is a coefficient of the first-level low-frequency subband LL2a, L31 is a coefficient of the first-level vertical mid-high-frequency subband HL2a, L32 is a coefficient of the first-level horizontal mid-high-frequency subband LH2a, and L33 is a coefficient of the first-level high-frequency subband HH2a, respectively.
L30=B0+B1+B2+B3;L31=B0+B1-B2-B3;
L32=B0-B1+B2-B3;L33=B0-B1-B2+B3。
The invention adopts two-stage wavelet transformation, the first stage wavelet transformation adopts 2-dimensional transformation (2 x 2 blocks), and the second stage wavelet transformation adopts 1-dimensional transformation (1*4 blocks). The 2-dimensional wavelet transformation mode and the 1-dimensional wavelet transformation mode only need 2 lines of buffer areas and addition and subtraction shift operation, the cost is low, and the robustness of the watermark is high.
In step S4, as shown in fig. 4, a two-level wavelet transform is performed, and a 1-dimensional haar wavelet transform is performed on the primary low-frequency subband LL1 by using 1*4 pixel blocks as units to obtain 4 second-level subbands. For example, the primary low-frequency subband LL1 is a pixel matrix of, for example, 32×32 (32 rows by 32 columns), and 4 coefficient matrices of 32×8 secondary subbands are obtained. The 4 second-level subbands are a second-level low-frequency subband LL2b, a second-level vertical mid-high-frequency subband HL2b, a second-level horizontal mid-high-frequency subband LH2b, and a second-level high-frequency subband HH2b, respectively. The calculation method is as follows:
C0, C1, C2, C3 are pixel values of 4 pixels of 1*4 pixel blocks in the first-level low-frequency subband LL1, L00 is a coefficient of the second-level low-frequency subband LL2b, L01 is a coefficient of the second-level vertical mid-high-frequency subband HL2b, L02 is a coefficient of the second-level horizontal mid-high-frequency subband LH2b, and L03 is a coefficient of the second-level high-frequency subband HH2b, respectively.
L00=C0+C1+C2+C3;L01=C0+C1-C2-C3;
L02=C0-C1+C2-C3;L03=C0-C1-C2+C3。
S5, calculating a low-frequency band pixel average value LL in the second-level low-frequency sub-band LL2b, and respectively obtaining the watermark intensity alpha of each embedded YUV three channels according to the corresponding relation between the low-frequency band pixel average value LL and the watermark intensity amplitude Z. Specifically, the low-band pixel average value LL, LL=L00/16 is calculated, and L00=C0+C1+C2+C3, namely L00 is the superposition of four pixels in the first-level low-frequency sub-band LL1, and each pixel in the first-level low-frequency sub-band LL1 is the superposition of four pixels A0, A1, A2 and A3 embedded in the channel C, so that L00 is equivalent to the low-band pixel average value LL which comprises 16 pixels embedded in the channel C, and the L00 of the frequency domain is divided by 16 to be the time domain. In this example, the parameter value in the frequency domain is divided by 16 to obtain the corresponding parameter value in the time domain, and the parameter value in the time domain is multiplied by 16 to obtain the corresponding parameter value in the frequency domain.
Fig. 5 is a watermark strength table, and fig. 6 is a plot of watermark strength magnitude Z against low band pixel average value LL. The watermark intensity table in fig. 5 is a relatively typical value obtained from a number of experiments. The specific values in the table of fig. 5 are not limited, and may be adjusted according to practical situations. The first column in fig. 5 shows k+1 (for example, k+1 is illustrated by 8 as an example) typical low-band pixel average values LL (x 0-x7), and the value range of the low-band pixel average values LL is 0 to 255. The second column in fig. 5 shows the watermark strength amplitude Z of the 8Y-channel embedded watermark corresponding to the 8 more typical low band pixel averages LL. The third column in fig. 5 shows the watermark strength magnitudes Z of 8U-channel and V-channel embedded watermarks corresponding to the 8 more typical low-band pixel averages LL, which are equal. The watermark intensity amplitude of the Y channel corresponding to the same typical value is smaller than that of the U channel or the V channel.
The calculation formula of the watermark intensity amplitude Z with respect to the low-band pixel average value LL is as follows:
as can be seen from the above formula, when the calculated average value ll+.x 0(x0 of the low-band pixels is 4), the watermark intensity amplitude of the corresponding Y-channel embedded watermark is a constant value Y 0(y0, for example, 0.16), and the watermark intensity amplitudes of the corresponding U-channel and V-channel embedded watermarks are a constant value Y 0(y0, for example, 0.33).
X 0 < calculated low-band pixel average LL < x 7, the watermark strength magnitude Z of the embedded watermark can be understood as a short line segment with a slope. For example, LL is interpolated into a corresponding one of the intervals (x n-1,xn) based on the magnitude of the average value LL of the low-band pixels calculated by ll=l00/16, for example, calculated as LL is 25,25 is inserted into the interval (x 1,x2), x 1 is 12, for example, and x 2 is 28, for example. A straight line is determined by two points (x n-1,yn-1) and (x n,yn), for example, an exemplary straight line is determined by two points (x 1,y1) and (x 2,y2), and the ordinate of the LL point corresponding to the straight line is calculated to be the watermark intensity amplitude Z. For the Y channel, Y n-1 and Y n of the second column of FIG. 5 are taken, and for the U and V channels, Y n-1 and Y n of the third column of FIG. 5 are taken. For the Y channel, a first ordinate corresponding to an abscissa 25 on a first straight line is calculated by utilizing the first straight line determined by the two points of the point (12,0.22) and the point (28,0.30), and the first ordinate is the watermark intensity amplitude Z of the embedded watermark of the Y channel corresponding to the low-frequency pixel average value LL of 25. For the U/V channel, a second ordinate corresponding to an abscissa 25 on a second straight line is calculated by utilizing a second straight line determined by two points (12,0.42) and (28,0.48), wherein the second ordinate is the watermark intensity amplitude Z of the U/V channel embedded watermark corresponding to a low-frequency pixel average value LL, for example, 25.
The average value LL Σ k(xk of the pixels in the low-band is, for example, 188), the watermark intensity amplitude of the corresponding Y-channel embedded watermark is a constant value Y k(yk, for example, 0.63), and the watermark intensity amplitude of the corresponding U-channel and V-channel embedded watermark is a constant value Y k(yk, for example, 0.99). The nonlinear watermark strength model is suitable for Y/U/V three channels.
As can be seen from fig. 6, the watermark intensity amplitude (blue curve) of the Y-channel embedded watermark corresponding to the average value LL of the same low-frequency band pixel is smaller than the watermark intensity amplitudes (yellow curve) of the U-channel and V-channel embedded watermarks, and the watermark intensity amplitude of the Y-channel embedded watermark is smaller, i.e., the Y-channel embedded watermark is weaker and is not easily seen by human eyes by adopting a strong constraint watermark intensity model. The watermark strength amplitude values of the U channel and the V channel embedded watermarks are larger, namely the U/V channel embedded watermark is relatively stronger by adopting a wide constraint watermark strength model.
The ordinate is interpolated from the interval of the watermark intensity table in fig. 5 and the calculation formula according to the low-band pixel average value LL, and is the watermark intensity amplitude Z of the embedded watermark. Setting the maximum variation of the pixel value of a pixel in the time domain caused by embedding the watermark as deltap, calculating the corresponding maximum watermark intensity value deltaN=deltap×16 in the frequency domain, and calculating the watermark intensity alpha=Z×deltaN.
Step S6, as shown in FIG. 7, according to the calculated watermark intensity, embedding the watermark into the first secondary high-frequency sub-band HH2a to obtain a watermark-carrying secondary high-frequency sub-band HH2a'. Specifically, the watermark embedding mode corresponding to each bit of the watermark is set as P, wherein P can be any-1, 1 sequence, and the quantity of-1, 1 is equal. P may also be a 2x 2 matrix with elements of-1/1 composition, and the sum of all elements is 0. An example of P is the following 2x 2 matrix:
illustratively, the first secondary high frequency sub-band HH2a is partitioned by 2 x2 blocks, and the watermark is embedded bit by bit into each block of the first secondary high frequency sub-band HH2 a. L33 'are coefficients of the watermark-carrying secondary high frequency sub-band HH2 a'. The watermark information is, for example, a combination of binary Bit numbers 0, 1. In each of the blocks of the block-by-block,
L33' =l33+p x alpha (if bit=1);
L33' =l33-p×alpha (if bit=0).
Because the human eyes have different perception degrees on the change of high-frequency and low-frequency components, the human eyes generally have high perception degrees on low frequency and relatively weak perception on high-frequency details, and therefore, the watermark is embedded into the high-frequency sub-band, so that the robustness and the concealment of the steganography algorithm are ensured.
S7, carrying out wavelet inverse transformation on all sub-bands containing the watermark-carrying second-level high-frequency sub-band HH2a' to obtain a watermark-carrying channel, and merging the YUV three channels carrying the watermark to obtain a watermark-carrying image. Specifically, as shown in FIG. 8, S71 performs 1-dimensional wavelet inverse transformation, namely, performs 1-dimensional haar wavelet inverse transformation on a first secondary low-frequency sub-band LL2a obtained by performing first-level high-frequency sub-band HH1 wavelet transformation, a first secondary vertical middle-high-frequency sub-band HL2a, a first secondary horizontal middle-high-frequency sub-band LH2a and a watermark-carrying secondary high-frequency sub-band HH2a 'to obtain an inverse transformation primary high-frequency sub-band HH1'.
B0', B1', B2', B3' are respectively the pixel values of 4 pixels of the 1*4 pixel block in the inverse transform primary high-frequency subband HH1', and L33' is the coefficient of the watermark-carrying secondary high-frequency subband HH2a '.
B0’=L30+L31+L32+L33’;B1’=L30+L31-L32-L33’;
B2’=L30-L31+L32-L33’;B3’=L30-L31-L32+L33’。
As shown in fig. 9, S72, performing 2-dimensional inverse wavelet transform on the first-level low-frequency sub-band LL1, the first-level vertical middle-high-frequency sub-band HL1, the first-level horizontal middle-high-frequency sub-band LH1, and the inverse-transformed first-level high-frequency sub-band HH1 'to obtain a watermark-carrying channel C', which is calculated as follows:
a0', A1', A2', A3' are the pixel values of 4 pixels of A2 x 2 pixel block in the watermark carrying channel C ', respectively, and L3' is the coefficient of the inverse transform primary high frequency subband HH1 '.
A0’=L0+L1+L2+L3';A1’=L0+L1-L2-L3';
A2’=L0-L1+L2-L3';A3’=L0-L1-L2+L3'。
By adopting the method, the watermark carrying channel can be obtained, only one channel of YUV three channels is embedded in the whole watermark embedding operation, and the specific embedding channel is set according to the actual requirement, and the watermark carrying channel and the two channels without the watermark are combined to obtain the watermark carrying image. Specifically, the two channels of the watermark carrying channel and the non-watermark carrying channel can be converted into RGB channels and then combined to obtain the watermark carrying image.
The invention discloses a YUV domain digital watermarking algorithm based on wavelet transformation, which further comprises watermark extraction, wherein the watermark extraction comprises the following steps:
As shown in fig. 10, the YUV channels of the watermark-carrying image are separated to obtain a watermark-carrying channel C ', where the watermark-carrying channel C' is any one of a watermark-carrying Y channel, a watermark-carrying U channel, and a watermark-carrying V channel.
And performing primary wavelet transformation, and performing 2-dimensional haar wavelet transformation on the watermark carrying channel C' by taking the 2 x2 pixel blocks as units to obtain 4 primary extraction sub-bands. The 4 primary extraction subbands are a primary extraction low-frequency subband LL1t, a primary extraction high-frequency subband HL1t in the vertical direction, a primary extraction high-frequency subband LH1t in the horizontal direction, and a primary extraction high-frequency subband HH1t, respectively. The calculation method is as follows:
A0', A1', A2', A3' are respectively pixel values of 4 pixels of 2 x 2 pixel blocks in the watermark carrying channel C ', T0 is a coefficient of primary extraction of a low-frequency sub-band LL1T, T1 is a coefficient of primary extraction of a high-frequency sub-band HL1T in the vertical direction, T2 is a coefficient of primary extraction of a high-frequency sub-band LH1T in the horizontal direction, and T3 is a coefficient of primary extraction of a high-frequency sub-band HH 1T.
T0=A0’+A1’+A2’+A3’;T1=A0’+A1’-A2’-A3’;
T2=A0’-A1’+A2’-A3’;T3=A0’-A1’-A2’+A3’。
As shown in fig. 11, the two-level wavelet transform is performed, and the first-level extracted high-frequency subband HH1t is subjected to 1-dimensional haar wavelet transform with 1*4 pixel blocks as units to obtain 4 two-level extracted subbands, namely a two-level extracted low-frequency subband LL2c, a two-level extracted vertical mid-high-frequency subband HL2c, a two-level extracted horizontal mid-high-frequency subband LH2c and a two-level extracted high-frequency subband HH2c. The calculation method is as follows:
D0, D1, D2, D3 are pixel values of 4 pixels of 1*4 pixel blocks in the first-order extraction high-frequency subband HH1T, T30 is a coefficient of the second-order extraction low-frequency subband TT2c, T31 is a coefficient of the second-order extraction high-frequency subband HT2c in the vertical direction, T32 is a coefficient of the second-order extraction high-frequency subband TH2c in the horizontal direction, and T33 is a coefficient of the second-order extraction high-frequency subband HH2c, respectively.
T30=D0+D1+D2+D3;T31=D0+D1-D2-D3;
T32=D0-D1+D2-D3;T33=D0-D1-D2+D3。
The coefficients in the secondary extracted high frequency subband HH2c are partitioned to obtain blocks of coefficient matrices, e.g. 2 x 2 blocks, each block being a 2 x 2 coefficient matrix. And sequentially calculating and extracting watermark Bit values corresponding to each coefficient matrix block, and splicing all the extracted watermark Bit values Bit to obtain a final watermark. In each coefficient matrix block, bit=1 if the result of the matrix point multiplication operation of the coefficient matrix block and the watermark embedding pattern P is >0, and bit=0 if the result of the matrix point multiplication operation of the coefficient matrix block and the watermark embedding pattern P is < 0.
Fig. 12 is a schematic diagram of watermark extraction accuracy under a lossless transmission channel. As shown in fig. 12, in the lossless transmission channel, the Bit Error Rate (BER) of the YUV three-channel watermark is 0, and the lower the Bit Error Rate, the higher the accuracy of the extracted watermark information. Under the channel of lossless transmission, the extraction accuracy of YUV three-channel watermarks reaches 100%.
Fig. 13 is a schematic diagram of watermark extraction accuracy under strong noise channel transmission. As shown in fig. 13, under the channel transmission of strong noise (SNR <20 dB), the U/V channel watermark extraction accuracy can reach 100%, and the Y channel accuracy approaches 100%. The method has good robustness for different YUV data transmission conditions.
Fig. 14 is a first diagram of image quality for an original image, a watermark Y-channel, a watermark U-channel, and a watermark V-channel. Fig. 15 is a second schematic diagram of image quality of an original image, a watermark Y-channel, a watermark U-channel, and a watermark V-channel. As shown in fig. 14 and 15, the images of the watermark Y channel, the watermark U channel and the watermark V channel have no visual difference, the image quality is high, and the peak signal-to-noise ratio (PSNR) of the watermark images embedded on the different channels is higher than 38dB. The Y/U/V channels can each maintain high image quality (PSNR >38dB represents high quality).
In summary, the invention provides a YUV domain digital watermarking algorithm based on wavelet transformation, which comprises S1, separating an original image to obtain an embedded channel, wherein the embedded channel is any one channel of YUV three channels obtained by separating the original image, watermark embedding is only carried out on one channel of the YUV three channels, S2, carrying out primary haar wavelet transformation on the embedded channel to obtain four primary sub-bands, the four primary sub-bands sequentially comprise a primary low-frequency sub-band, a primary high-frequency sub-band in the vertical direction, a primary high-frequency sub-band in the horizontal direction and a primary high-frequency sub-band, S3, carrying out secondary haar wavelet transformation on the primary high-frequency sub-band to obtain four first secondary sub-bands, the four first secondary sub-bands comprise a first secondary sub-band, S4, carrying out secondary haar wavelet transformation on the primary low-frequency sub-band to obtain four second secondary sub-bands, the four secondary sub-bands comprise a secondary low-band, S5, calculating the average value of low-pixels in the secondary low-frequency sub-band, and the primary low-band, and carrying out watermark embedding is carried out on the primary low-frequency sub-band according to the LL sub-carrier, and the primary watermark is obtained, and the watermark is not carried out on the primary watermark, and the primary watermark is obtained by carrying out the watermark embedding relation between the primary high-frequency sub-band and the carrier watermark.
The invention adopts two-stage wavelet transformation, only needs 2 lines of buffer areas and addition and subtraction shift operation, and has lower cost. Aiming at YUV visual characteristics, YUV three channels are designed with different intensity curves, and watermark embedding in any channel in YUV can obtain better image quality. The load is high, longer information can be hidden, and the Y channel has twice the hiding capacity of the U/V channel, so that the higher load requirement can be met. The robustness is high, and the high accuracy is still achieved under the strong noise transmission channel.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the method disclosed in the embodiment, the description is relatively simple since it corresponds to the device disclosed in the embodiment, and the relevant points refer to the description of the method section.
The foregoing description is only illustrative of the preferred embodiments of the present invention, and is not intended to limit the scope of the claims, and any person skilled in the art may make any possible variations and modifications to the technical solution of the present invention using the method and technical content disclosed above without departing from the spirit and scope of the invention, so any simple modification, equivalent variation and modification made to the above embodiments according to the technical matter of the present invention fall within the scope of the technical solution of the present invention.
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Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20040208339A1 (en) * | 2003-01-15 | 2004-10-21 | Yasushi Abe | Image processing apparatus, program, and storage medium that can selectively vary embedding specification of digital watermark data |
US20070140524A1 (en) * | 2005-12-21 | 2007-06-21 | Sanjeev Kumar | Image Watermarking Based on Sequency and Wavelet Transforms |
CN102496135A (en) * | 2011-12-06 | 2012-06-13 | 银江股份有限公司 | Deadweight tonnage (DWT) domain-based digital watermark method and system |
CN103413266A (en) * | 2013-07-02 | 2013-11-27 | 济南大学 | Blind watermark method in wavelet domain |
CN109447889A (en) * | 2018-11-22 | 2019-03-08 | 央视国际网络无锡有限公司 | A method of realizing concealed video digital watermark |
CN111445374A (en) * | 2018-12-29 | 2020-07-24 | 北京奇虎科技有限公司 | Watermark template generation method and device for embedding hidden digital watermark into image |
CN112907435A (en) * | 2021-04-09 | 2021-06-04 | 辽宁工程技术大学 | High-robustness holographic blind watermarking algorithm based on improved Boqi coding and data interval mapping |
CN115695825A (en) * | 2022-11-03 | 2023-02-03 | 豪威科技(武汉)有限公司 | Hidden watermark writing method and readable storage medium |
CN117522666A (en) * | 2023-11-20 | 2024-02-06 | 深圳市证通电子股份有限公司 | Method and device for embedding and extracting invisible digital watermark in image |
CN117670637A (en) * | 2023-11-30 | 2024-03-08 | 华南理工大学 | Image blind watermark embedding and complete extraction method based on strong robust multi-domain transformation |
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20040208339A1 (en) * | 2003-01-15 | 2004-10-21 | Yasushi Abe | Image processing apparatus, program, and storage medium that can selectively vary embedding specification of digital watermark data |
US20070140524A1 (en) * | 2005-12-21 | 2007-06-21 | Sanjeev Kumar | Image Watermarking Based on Sequency and Wavelet Transforms |
CN102496135A (en) * | 2011-12-06 | 2012-06-13 | 银江股份有限公司 | Deadweight tonnage (DWT) domain-based digital watermark method and system |
CN103413266A (en) * | 2013-07-02 | 2013-11-27 | 济南大学 | Blind watermark method in wavelet domain |
CN109447889A (en) * | 2018-11-22 | 2019-03-08 | 央视国际网络无锡有限公司 | A method of realizing concealed video digital watermark |
CN111445374A (en) * | 2018-12-29 | 2020-07-24 | 北京奇虎科技有限公司 | Watermark template generation method and device for embedding hidden digital watermark into image |
CN112907435A (en) * | 2021-04-09 | 2021-06-04 | 辽宁工程技术大学 | High-robustness holographic blind watermarking algorithm based on improved Boqi coding and data interval mapping |
CN115695825A (en) * | 2022-11-03 | 2023-02-03 | 豪威科技(武汉)有限公司 | Hidden watermark writing method and readable storage medium |
CN117522666A (en) * | 2023-11-20 | 2024-02-06 | 深圳市证通电子股份有限公司 | Method and device for embedding and extracting invisible digital watermark in image |
CN117670637A (en) * | 2023-11-30 | 2024-03-08 | 华南理工大学 | Image blind watermark embedding and complete extraction method based on strong robust multi-domain transformation |
Non-Patent Citations (2)
Title |
---|
ZORAN S 等: "A Secured Digital Video Watermarking in Chrominance Channel", 2018 23RD INTERNATIONAL SCIENTIFIC-PROFESSIONAL CONFERENCE ON INFORMATION TECHNOLOGY (IT), 31 December 2018 (2018-12-31), pages 1 - 4 * |
苗鑫梅 等: "可携带图像特性信息的双盲水印设计与实现", 计算机工程与设计, vol. 40, no. 5, 31 May 2019 (2019-05-31), pages 1225 - 1230 * |
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