CN103996164A - Medical image zero watermarking embedding and extracting method based on real fractional Fourier transform - Google Patents

Abstract

The invention discloses a medical image zero watermarking embedding and extracting method based on real fractional Fourier transform and belongs to the technical field of information safety and image processing. According to the medical image zero watermarking embedding and extracting method based on the real fractional Fourier transform, the own characteristics of an image are utilized for structuring watermark information rather than modified, it is guaranteed that original image information does not change in the embedding process of a watermark, the embedded information amount is large, and the demands of authenticity and reliability of medical images are met. The method combines the real fractional Fourier transform theory, the image encryption theory and the zero watermarking technology, on the premise that high fidelity characteristics of the medical images are guaranteed, the robustness and the safety of the watermark are taken into consideration, the algorithm is simple and fast, realization cost is low, and the method has high practical value.

Description

Medical image based on real fractional fourier transform zero watermark embedding and extracting method

Technical field

The invention belongs to information security and technical field of image processing, be specifically related to a kind of medical image based on real fractional fourier transform zero watermark embedding and extracting method.

Background technology

Along with the development of Internet technology, digital multimedia product is in the process that stores, propagates, uses, more and more easily by malicious attack, illegally usurp; For digital multimedia product, how effectively and expediently to protect copyright, become problem demanding prompt solution; Digital watermark technology is the effective ways of realizing copyright protection, and its basic thought is not affect under the service condition of digital multimedia, embeds in confidence valuable information in digital medium information, thereby reaches the object of the copyright protection of digital product.

Medical image, as the important evidence of clinical diagnosis, is being brought into play extremely important effect at aspects such as clinical, scientific research, teaching; Medical image requires, when it is carried out to copyright protection, can not destroy original image information.Because common digital watermark technology has all changed the feature of original image more or less, can not meet the demand of medical image high-fidelity, therefore, be badly in need of seeking a kind of new copyright protection means for medical image.

The existing method for medical image copyright protection mainly contains: reversible medical science watermarking algorithm, based on non-area-of-interest medical science watermarking algorithm, compressed Domain Watermarking Algorithm etc.; What reversible medical science watermarking algorithm mainly adopted is a kind of reversible thoughtcast,, after watermark extracting, image can be reduced into original state without distortion, thereby eliminated, embeds caused distortion because of watermark; Although reversible digital watermarking has the advantage of himself, embeddable data volume is very little, and safety coefficient is not high, and the protection of medical image is also only existed in transmitting procedure, once incoming terminal just reverts to virgin state, no longer has protective effect; Based on non-area-of-interest medical science watermarking algorithm, be that watermark information is embedded in the non-area-of-interest of medical image; Because medical image is black background mostly, therefore information capacity is very limited, and the searching process of the non-area-of-interest of medical image is very loaded down with trivial details, conventionally needs manual intervention to complete, and has increased complexity and the workload of algorithm; Medical science watermarking algorithm based on compression domain is embed watermark in compression domain, namely watermark is directly embedded in the bit stream after compression coding.The advantage of this algorithm is the Code And Decode process of having avoided a large amount of, thereby computation complexity is lower, can not cause the decline of medical image quality, and has given full play to temporal advantage; Yet because the restriction of compression bit rate defines the data volume size that watermark embeds, embedding grammar also will be subject to the restriction of corresponding image compression algorithm standard.

Summary of the invention

Shortcoming for prior art, the present invention proposes a kind of medical image based on real fractional fourier transform zero watermark embedding and extracting method, constant to reach in the telescopiny of watermark original image information, meet the authenticity of medical image and the demand of reliability, reduce costs, improve the object of security and practicality.

Medical image based on real fractional fourier transform zero watermark embedding and an extracting method, comprises the following steps:

Step 1, pre-service medical image is carried out to matrixing processing, obtain the picture element matrix of this medical image, the line number of this matrix is the line number of image slices vegetarian refreshments, and this matrix column number is the columns of image slices vegetarian refreshments, and this entry of a matrix element is the pixel value of pixel;

Step 2, watermarking images is carried out to matrixing processing, obtain the picture element matrix of this watermarking images, the line number of this matrix is the line number of watermarking images pixel, and this matrix column number is the columns of watermarking images pixel, and this entry of a matrix element is the pixel value of pixel;

Step 3, medical image and watermarking images after matrixing is processed carry out respectively real fractional fourier transform, obtain the frequency domain value of each pixel, and then obtain medical image picture element matrix after conversion and the watermarking images picture element matrix after conversion,

Step 4, by conversion after medical image picture element matrix in element scan by column, obtain the vector of a line multiple row, this vectorial columns is the number of element in medical image picture element matrix, element in vector is sorted from small to large, and the position of element in former vector in the vector after definite sequence, acquisition primary importance vector, stores primary importance vector as the first key;

Step 5, by conversion after watermarking images picture element matrix in element scan by column, obtain the vector of a line multiple row, this vectorial columns is the number of element in watermarking images picture element matrix, element in vector is sorted from small to large, and the position of element in former vector in the vector after definite sequence, acquisition second place vector, stores second place vector as the second key;

Step 6, determine the position in the vector of element after medical image sequence in the vector after watermarking images sequence, obtain the 3rd position vector, the 3rd position vector is stored as the 3rd key, complete zero watermark embed process;

Step 7, according to the actual requirements, when needs extract watermarking images, pre-service medical image is carried out to matrixing processing, obtain the picture element matrix of this medical image, the line number of this matrix is the line number of image slices vegetarian refreshments, this matrix column number is the columns of image slices vegetarian refreshments, and this entry of a matrix element is the pixel value of pixel;

Step 8, extract stored all keys, the medical image after matrixing is processed carries out real fractional fourier transform, obtains the frequency domain value of each pixel, and then obtains the medical image picture element matrix after conversion;

Step 9, by conversion after medical image picture element matrix in element scan by column, obtain the vector of a line multiple row, this vectorial columns is the number of element in medical image picture element matrix, and the element in vector is sorted according to the first key, obtains the vector after sequence;

Step 10, according to the 3rd key, in the vector after sequence, extract to obtain the vector after watermarking images sequence;

Step 11, according to the second key, the element in vector after watermarking images sequence is carried out to reversed arrangement, and element in the vector after reversed arrangement is reverted to matrix form;

Step 12, the watermarking images matrix after recovering is carried out to real fraction Fourier inverse transformation, obtain the time thresholding of a pixel, the matrix after conversion is original watermark image picture element matrix, completes the extraction to embed watermark image.

Position in vector after definite watermarking images sequence described in step 6 in the vector of element after medical image sequence, if a certain element is not present in the vector after medical image sequence in the vector after watermarking images sequence, the vector after medical image sequence is found with it big or small immediate element position.

Real fraction Fourier inverse transformation described in step 12, is the real fractional Fourier transform that conversion exponent number value is the opposite number of real fractional Fourier transform conversion exponent number in step 3.

Advantage of the present invention:

1, reversible medical science watermarking algorithm main thought is after watermark extracting; image can be reduced into original state without distortion; thereby eliminated, embed caused distortion because of watermark; but embeddable data volume is very little; and safety coefficient is not high, the protection of medical image is also only existed in transmitting procedure, once incoming terminal; just revert to virgin state, no longer there is protective effect.The data volume embedding in theory of algorithm proposed by the invention can be infinitely great, and adopt a plurality of keys to guarantee the security of data, no matter, in transmitting procedure or in data terminal, can reach protective effect.

2, based on non-area-of-interest medical science watermarking algorithm, be that watermark information is embedded in the non-area-of-interest of medical image; Because medical image is black background mostly, therefore information capacity is very limited, and the searching process of the non-area-of-interest of medical image is very loaded down with trivial details, conventionally needs manual intervention to complete, and has increased complexity and the workload of algorithm; The algorithm that the present invention proposes is adaptive algorithm, without manual intervention, automatically in best mode, reaches the object of copyright protection, embeds algorithm compare with non-area-of-interest, and the present invention is more prone to realize.

3, the medical science watermarking algorithm based on compression domain is embed watermark in compression domain, namely watermark is directly embedded in the bit stream after compression coding.The advantage of this algorithm is the Code And Decode process of having avoided a large amount of, thereby computation complexity is lower, can not cause the decline of medical image quality, and has given full play to temporal advantage; Yet because the restriction of compression bit rate defines the data volume size that watermark embeds, embedding grammar also will be subject to the restriction of corresponding image compression algorithm standard; This algorithm is not subject to the restriction of any image compression algorithm, and the result of simultaneously calculating is real number, is more conducive to transmission and the storage of data.

In sum, the present invention utilizes the unique characteristics of image to construct watermark information, rather than revises these features of image, and it can guarantee that original image information is constant in the telescopiny of watermark, and the quantity of information embedding is larger, has met the authenticity of medical image and the demand of reliability; It is theoretical that real fractional fourier transform has been merged in the present invention, and the theoretical and zero digital watermark of image encryption, is guaranteeing under the prerequisite of medical image high-fidelity characteristic, robustness and the security of watermark have been taken into account, algorithm is simple and quick, realizes with low costly, has very strong practical value.

Accompanying drawing explanation

Fig. 1 is zero watermark embedding and the extracting method process flow diagram of the medical image based on real fractional fourier transform of an embodiment of the present invention;

Fig. 2 is the Cranial Computed Tomography image of an embodiment of the present invention;

Fig. 3 is the watermarking images of the required embedding of an embodiment of the present invention;

Fig. 4 is the CT image after the real fractional fourier transform of an embodiment of the present invention;

Fig. 5 is the watermarking images after the real fractional fourier transform of an embodiment of the present invention;

Fig. 6 is the watermarking images of the extraction of an embodiment of the present invention;

Fig. 7 is that the Gaussian noise of an embodiment of the present invention is attacked experimental results schematic diagram, wherein, figure (a) for variance be 0.003 o'clock extraction watermarking images, figure (b) for variance be 0.006 o'clock extraction watermarking images, figure (c) for variance be the watermarking images extracting for 0.009 o'clock, figure (d) for variance be the watermarking images of extraction in 0.03 o'clock;

Fig. 8 is that the salt-pepper noise of an embodiment of the present invention is attacked experimental results schematic diagram, wherein, figure (a) for noise intensity be 0.03 o'clock extraction watermarking images, figure (b) for noise intensity be the watermarking images extracting for 0.05 o'clock, figure (c) for noise intensity be the watermarking images of extraction in 0.08 o'clock;

Fig. 9 is that the JPEG lossy compression method of an embodiment of the present invention is attacked experimental results schematic diagram, wherein, figure (a) for JPEG quality factor be 90 o'clock extraction watermarking images, figure (b) for JPEG quality factor be 60 o'clock extraction watermarking images, figure (c) for JPEG quality factor be 30 o'clock extraction watermarking images, figure (d) for JPEG quality factor be the watermarking images extracting for 10 o'clock, figure (e) for JPEG quality factor be the watermarking images of extraction in 5 o'clock;

Figure 10 is that the Gassian low-pass filter of an embodiment of the present invention is attacked experimental results schematic diagram, wherein, figure (a) for standard deviation be 0.5 o'clock extraction watermarking images, figure (b) for standard deviation be the watermarking images extracting for 0.7 o'clock, figure (c) for standard deviation be the watermarking images of extraction in 0.9 o'clock.

Embodiment

Below in conjunction with accompanying drawing, an embodiment of the present invention is described further.

In the embodiment of the present invention, adopt adaptive zero-watermarking based on real fractional fourier transform to embed and extracting method reaches the object of the copyright protection of medical image.The present invention is applied to the end of CT machine imaging; by processing of the present invention; CT machine can be by patient's natural situation; the important informations such as diagnosis report are hidden in produced CT image; thereby reach the copyright protection object to produced CT image; both be conducive to protect patient's privacy, can when there is dispute over copyright, provide important legal basis again.

Medical image based on real fractional fourier transform zero watermark embedding and an extracting method, the process flow diagram of method as shown in Figure 1, comprises the following steps:

Step 1, pre-service medical image is carried out to matrixing processing, obtain the picture element matrix X=(x of this medical image _{m, n}) _{m * N}, the line number of this matrix is the line number M of image slices vegetarian refreshments, the columns N that this matrix column number is image slices vegetarian refreshments, this entry of a matrix element x _{m, n}pixel value for pixel;

In the embodiment of the present invention, the width Cranial Computed Tomography image of take is example, as shown in Figure 2, reads this image, and image is gray level image, and size is 256 * 256, x _{m, n}∈ [0,255];

Step 2, watermarking images is carried out to matrixing processing, obtain the picture element matrix W=(w of this watermarking images _{i, j}) _{l * R}, the line number of this matrix is the line number L of watermarking images pixel, the columns R that this matrix column number is watermarking images pixel, this entry of a matrix element w _{i, j}pixel value for pixel;

Watermarking images can be the important informations such as patient's natural situation, diagnosis report, and in the embodiment of the present invention, the head portrait of take is illustrated as example as watermarking images.As shown in Figure 3, read this Gray-level Watermarking image, size is 64 * 64, pictorial element w _{i, j}span be [0,255].

Step 3, the medical image X=(x after matrixing is processed _{m, n}) _{m * N}with watermarking images W=(w _{i, j}) _{l * R}carry out respectively real fractional fourier transform, obtain the frequency domain value of each pixel, and then obtain the medical image picture element matrix Y=(y after conversion _{m, n}) _{m * N}with the watermarking images picture element matrix Z=(z after conversion _{i, j}) _{l * R}; y _{m, n}element for the m of matrix Y is capable, on n column position, y _{m, n}for real number; z _{i, j}element for the i of watermarking images Z is capable, on j column position, z _{i, j}for real number.

Specific as follows:

Build fractional fourier transform formula as follows:

Wherein, represent fractional fourier transform operator, α represents fractional fourier transform exponent number, and span is (0,1); F (t) represents a continuous signal, and t represents the time; κ _α(u, t) represents transformation kernel function, and formula is as follows:

${\mathrm{\κ}}_{\mathrm{\α}}(u,t)=\left\{\begin{array}{cc}\sqrt{\frac{1-j\cot \mathrm{\φ}}{2\mathrm{\π}}}\exp (j\frac{t^2+u^2}{2}\cot \mathrm{\φ}-\mathrm{jut}\csc \mathrm{\φ}),& \mathrm{\φ}\≠\mathrm{n\π}\\ \mathrm{\δ}(t-u),& \mathrm{\φ}=2\mathrm{n\π}\\ \mathrm{\δ}(t+u),& \mathrm{\φ}=(2n\±1)\mathrm{\π}\end{array}\right.---\left(2\right)$

Wherein, u represents α score field, and exp (.) represents the exponential of e; φ=α pi/2 represents the angle of phase rotating, and j represents imaginary part; N represents positive integer; δ () represents shock response

The fractional fourier transform formula of structure is carried out to discretize processing, obtains discrete fraction Fourier transform:

Wherein, v _kbe an orthonormal proper vector, and require proper vector v _kbe similar to the fundamental function (Hermite-Gaussian function continuously) of Fourier transform.

According to formula (3), obtain real discrete fraction Fourier transform:

$\begin{array}{c}y=\left[\begin{array}{c}\mathrm{Re}\left(F^{\mathrm{\α}}\right)\mathrm{Re}\left(\hat{x}\right)-\mathrm{Im}\left(F^{\mathrm{\α}}\right)\mathrm{Im}\left(\hat{x}\right)\\ \mathrm{Im}\left(F^{\mathrm{\α}}\right)\mathrm{Re}\left(\hat{x}\right)+\mathrm{Re}\left(F^{\mathrm{\α}}\right)\mathrm{Im}\left(\hat{x}\right)\end{array}\right]=\left[\begin{array}{cc}\mathrm{Re}\left(F^{\mathrm{\α}}\right)& -\mathrm{Im}\left(F^{\mathrm{\α}}\right)\\ \mathrm{Im}\left(F^{\mathrm{\α}}\right)& \mathrm{Re}\left(F^{\mathrm{\α}}\right)\end{array}\right]\left[\begin{array}{c}\mathrm{Re}\left(\hat{x}\right)\\ \mathrm{Im}\left(\hat{x}\right)\end{array}\right]\\ {=R}^{\mathrm{\α}}\·x\end{array}---\left(4\right)$

Wherein, Re () represents real part; Im () represents imaginary part; X={x ₁, x ₂, x ₃..., x _n} ^trepresent the signal that length is N, N is even number;

From above, can obtain real fractional fourier transform matrix is:

$R^{\mathrm{\α}}=\left[\begin{array}{cc}\mathrm{Re}\left(F^{\mathrm{\α}}\right)& -\mathrm{Im}\left(F^{\mathrm{\α}}\right)\\ \mathrm{Im}\left(F^{\mathrm{\α}}\right)& \mathrm{Re}\left(F^{\mathrm{\α}}\right)\end{array}\right]---\left(5\right)$

The medical image picture element matrix that substitution is to be transformed or watermarking images picture element matrix, the real fractional fourier transform of structure two-dimensional discrete is:

$Y=R^{({\mathrm{\α}}_L,{\mathrm{\α}}_R)}\left[X\right]=R^{{\mathrm{\α}}_L}\·X\·R^{{\mathrm{\α}}_R}---\left(6\right)$

represent two-dimentional real fractional fourier transform operator; X represents medical image picture element matrix to be transformed or watermarking images picture element matrix; represent the real fractional fourier transform matrix of N * N; represent the real fractional fourier transform matrix of M * M, α _land α _rbe respectively two-dimentional real fractional fourier transform exponent number, in the embodiment of the present invention, α _lfor α (alpha), α _rfor β (beta); Y represent conversion after medical image picture element matrix or conversion after watermarking images picture element matrix;

In the embodiment of the present invention, CT image is carried out to real fractional fourier transform, conversion coefficient alpha in real fractional fourier transform, the span of beta is [0,1], increase along with conversion coefficient, image is changed to frequency domain by time domain gradually, and conversion coefficient can be chosen as required voluntarily, chooses alpha=0.3 here, beta=0.3, the result of conversion is as shown in Figure 4;

In the embodiment of the present invention, watermarking images is carried out to real fractional fourier transform, the conversion coefficient in real fractional fourier transform is with identical to the coefficient of CT image conversion, i.e. alpha=0.3, and beta=0.3, the result of conversion is as shown in Figure 5.

Step 4, by conversion after medical image picture element matrix Y=(y _{m, n}) _{m * N}in element scan by column, obtain the vectorial Y ' of a line multiple row=(y ' _{1, mn}) _{1 * MN}, this vectorial columns is the number of element in medical image picture element matrix, the element in vector is sorted from small to large, and determine the vectorial Y after sequence _s'=(y _s' _{1, mn}) _{1 * MN}the position of middle element in former vector, obtains primary importance vector P=(p _{1, mn}) _{1 * MN}, primary importance vector is stored as the first key;

Wherein, Y '=(y ' _{1, mn}) _{1 * MN}for the vector of M * N row, y ' _{1, mn}the locational element of the m * n for vectorial Y '; P is that size is 1 row, the vector of M * N row, p _{1, mn}the locational element of the m * n for vectorial P; Y _s' be that size is 1 row, the vector of M * N row, y _s' _{1, mn}for vectorial Y _s' the locational element of the m * n;

In the embodiment of the present invention, Fig. 4 is scanned by column, obtain 1 row, the vector of 65536 row, this vector is carried out to ascending order arrangement, record the position of each element vectorial after arranging in former vector simultaneously, these positional informations form one group of vector and store as the first key;

Suppose that Fig. 4 is matrix $\left[\begin{array}{ccc}6& 2& 4\\ 3& 1& 9\\ 5& 7& 8\end{array}\right],$ After scanning, be [6 3521749 8], ascending order is arranged as [1 2345678 9], record the first key P=[5 4273169 8];

Step 5, the element in the watermarking images picture element matrix after conversion is scanned by column, obtain the vector Z of a line multiple row '=(z ' _{1, ij}) _{1 * LR}, this vectorial columns is the number of element in watermarking images picture element matrix, the element in vector is sorted from small to large, and determine the vector Z after sequence _s'=(z _s' _{1, ij}) _{1 * LR}the position of middle element in former vector, obtains second place vector P ^w=(p ^w _{1, ij}) _{1 * LR}, second place vector is stored as the second key;

Wherein, Z ' is that size is 1 row, the vector of L * R row, z ' _{1, ij}for vector Z ' the locational element of the i * j; Z _s' be that size is 1 row, the vector of L * R row, z _s' _{1, ij}for vector Z _s' the locational element of the i * j; P ^wthat size is 1 row, the vector of L * R row, p _{1, ij}for vectorial P ^wthe locational element of the i * j;

In the embodiment of the present invention, Fig. 5 is scanned by column, obtain 1 row, the vector of 4096 row, this vector is carried out to ascending order arrangement, record the position of each element vectorial after arranging in former vector simultaneously, these positional informations form one group of vector and store as the second key;

Suppose that Fig. 5 is matrix $\left[\begin{array}{cc}2& 6\\ 8& 3\end{array}\right],$ After scanning, be [2 86 3], ascending order is arranged as [2 36 8], record the second key P ^w=[1 43 2];

Step 6, determine the vectorial z ' after watermarking images sequence _{1, ij}the vectorial Y of middle element after medical image sequence _s'=(y _s' _{1, mn}) _{1 * MN}in position, obtain the 3rd position vector Q=(q _{1, ij}) _{1 * LR}, the 3rd position vector is stored as the 3rd key, complete zero watermark embed process; Wherein, q _{1, ij}the locational element of the i * j for vectorial Q;

In the embodiment of the present invention, at the vectorial Y of step 4 gained _s'=(y _s' _{1, mn}) _{1 * MN}in find with step 5 vectorial z ' _{1, ij}the immediate element y of each element value _s' _{1, mn}, and record these elements embed step 6 vector in position, these positional informations form one group of vector and store as the 3rd key;

In the embodiment of the present invention, [2 36 8] corresponding position in [1 2345678 9] is the 3rd key Q=[2 36 8];

Register all keys, store.Original Cranial Computed Tomography image is showing no sign of in impaired situation, has completed adaptive zero-watermarking and has embedded algorithm, and the medical image that CT machine produces will as a result of be exported.

Step 7, according to the actual requirements, when needs extract watermarking images, carries out matrixing processing by pre-service medical image, obtains the picture element matrix X=(x of this medical image _{m, n}) _{m * N}, the line number of this matrix is the line number of image slices vegetarian refreshments, and this matrix column number is the columns of image slices vegetarian refreshments, and this entry of a matrix element is the pixel value of pixel; x _{m, n}element for the m of medical image X is capable, on n column position, x _{m, n}∈ [0,255];

In the embodiment of the present invention, when occurring the problems such as dispute over copyright, when copyright owner need to prove the legitimacy of copyright, can extract watermark information;

Step 8, extract stored all key alpha, beta, L, R, P, P ^w, Q, the medical image after matrixing is processed carries out real fractional fourier transform, obtains the frequency domain value of each pixel, and then obtains the medical image picture element matrix after conversion;

To image X=(x to be extracted _{m, n}) _{m * N}carry out real fractional fourier transform, the coefficient in real fractional fourier transform is alpha, and beta obtains matrix Y=(y _{m, n}) _{m * N}.Wherein, Y is that size is the matrix of M * N, the row of M representing matrix, the row of N representing matrix, y _{m, n}element for the m of matrix Y is capable, on n column position, y _{m, n}for real number; In the embodiment of the present invention, the Cranial Computed Tomography image reading is carried out to real fractional fourier transform, the coefficient in real fractional fourier transform is alpha=0.3, and beta=0.3 obtains image after the real fractional fourier transform of Cranial Computed Tomography image.

Step 9, the element in the medical image picture element matrix after conversion is scanned by column, obtain the vectorial Y ' of a line multiple row=(y ' _{1, mn}) _{1 * MN}, this vectorial columns is the number of element in medical image picture element matrix, and the element in vector is sorted according to the first key, obtains the vectorial Y after sequence _s'=(y _s' _{1, mn}) _{1 * MN};

In the embodiment of the present invention, the CT image after real fractional fourier transform is scanned by column, obtain 1 row, the vector of 65536 row, utilizes the first key to resequence to this vector;

For example, will $\left[\begin{array}{ccc}6& 2& 4\\ 3& 1& 9\\ 5& 7& 8\end{array}\right],$ After scanning, obtain [6 3521749 8], utilize P=[5 4273169 8] rearrange and obtain [1 2345678 9];

Step 10, according to the 3rd key, in the vector after sequence, extract to obtain the vector after watermarking images sequence;

At Y _s' in, extract { q _{1, ij}| q _{1, ij}element on ∈ Q} position, by the synthetic Z of these element set _s'=(z _s' _{1, ij}) _{1 * LR}, wherein, Z _s' be that size is 1 row, the vector of L * R row, z _s' _{1, ij}for vector Z _s' the locational element of the i * j; In the embodiment of the present invention, in the vector of rearrangement, extract the 3rd key and preserve element corresponding to position, these elements are reassembled into 1 row, the vector of 4096 row; For example, in [1 2345678 9] with Q=[2 36 8] extract element and obtain vector [2 36 8];

Step 11, according to the second key P ^w, by vector Z after watermarking images sequence _s' in element carry out reversed arrangement, and by the vector Z after reversed arrangement '=(z ' _{1, ij}) _{1 * LR}middle element reverts to matrix form Z=(z _{i, j}) _{l * R}; Wherein, Z ' is that size is 1 row, the vector of L * R row, z ' _{1, ij}for vector Z ' the locational element of the i * j; Wherein, the row of L representing matrix, the row of R representing matrix, z _{i, j}element for the i of watermarking images Z is capable, on j column position, z _{i, j}for real number;

For example, [2 36 8] are passed through to the second key P ^w=[1 43 2] reversed arrangement becomes [2 86 3];

And every 64 elements of the vector that just extracts gained form a line, altogether line up 64 row, obtain the matrix that a size is 64 * 64;

For example, [2 86 3] are arranged in matrix $\left[\begin{array}{cc}2& 6\\ 8& 3\end{array}\right];$

Step 12, the watermarking images matrix after recovering is carried out to real fraction Fourier inverse transformation, obtain the time thresholding of a pixel, the matrix after conversion is original watermark image picture element matrix, completes the extraction to embed watermark image.

Z is carried out to real Fractional Inverse Fourier Transform, and conversion coefficient is-alpha, the real fractional fourier transform of-beta, and obtaining size is the matrix W of L * R=(w _{i, j}) _{l * R}, wherein, the row of L representing matrix, the row of R representing matrix, w _{i, j}i that ∈ [0,255] is W is capable, the element on j column position.Matrix W is extracted watermarking images; In the embodiment of the present invention, the matrix that extracts gained is carried out to real Fractional Inverse Fourier Transform, conversion coefficient is alpha=-0.3, the real fractional fourier transform of beta=-0.3, transformation results is the watermarking images of extraction, as shown in Figure 6, completes the extraction to embed watermark image.

Innovative point of the present invention:

The present invention solves the protection problem of medical image with zero watermarking algorithm, creationary real fractional fourier transform is applied among zero watermarking algorithm, and innovation is mainly manifested in the following aspects:

1, traditional water mark method is that watermark information is embedded in original image, and this method more or less all can change original image feature.Due to the authenticity of medical image and the demand of reliability, traditional watermarking algorithm can not meet its requirement.The present invention proposes the Copyright Protection of a kind of new zero watermark embedding and extracting method solution medical image, realizes the object of copyright protection under the prerequisite of not damaging former medical image.

2, real fractional fourier transform being applied among zero watermarking algorithm of the invention, than the existing method for medical image copyright protection, the quantity of information of this algorithm embed watermark is larger, and attack tolerant can be stronger, and security is higher.

3, the result of calculation of traditional algorithm is plural number, and in this algorithm, the result of real fractional fourier transform is real number, is more beneficial to storage, transmission and processes, and also greatly reduces the complexity of algorithm simultaneously, makes invention be more prone to realize.

4, the asymmetric conversion coefficient of real fractional fourier transform can be used as key storage, has greatly strengthened the safety and reliability of algorithm.

Below in conjunction with multiple common attack mode, the robustness of this algorithm is tested:

In the embodiment of the present invention, adopt NC (normalized correlation coefficient) value to weigh the watermarking images of extraction and the otherness of original watermark image, when the watermarking images extracting is identical with original watermark image, the value of NC is that 1, NC is defined as:

$\mathrm{NC}=\frac{\underset{i,j}{\mathrm{\Σ}}{I}_{i,j}{I^{\′}}_{i,j}}{\underset{i,j}{\mathrm{\Σ}}{I^2}_{i,j}}---\left(7\right)$

Wherein, I _{i, j}represent original watermark image picture element matrix, I ' _{i, j}represent to extract watermarking images picture element matrix;

Through experiment, learn, the watermarking images (shown in Fig. 6) extracting when not receiving attack is 1 with the NC value of original watermark image (shown in Fig. 3), illustrates that the watermarking images of extraction is identical with original watermark image when not receiving attack.

Medical image is carried out to the polytypes such as noise, compression, shearing, the attack of multiple intensity, test robustness, experimental result gathers as shown in table 1 and Fig. 7 to Figure 10:

Table 1: multiple common attack experimental results

From experimental result, can find out, the watermark NC value that this algorithm can guarantee extraction to various common attack modes, more than 0.98, is compared with known medical image Watermarking algorithm for copyright protection, has stronger robustness.

Claims (3)

1. zero watermark embedding and the extracting method of the medical image based on real fractional fourier transform, is characterized in that, comprises the following steps:

Step 1, pre-service medical image is carried out to matrixing processing, obtain the picture element matrix of this medical image, the line number of this matrix is the line number of image slices vegetarian refreshments, and this matrix column number is the columns of image slices vegetarian refreshments, and this entry of a matrix element is the pixel value of pixel;

Step 2, watermarking images is carried out to matrixing processing, obtain the picture element matrix of this watermarking images, the line number of this matrix is the line number of watermarking images pixel, and this matrix column number is the columns of watermarking images pixel, and this entry of a matrix element is the pixel value of pixel;

Step 3, medical image and watermarking images after matrixing is processed carry out respectively real fractional fourier transform, obtain the frequency domain value of each pixel, and then obtain medical image picture element matrix after conversion and the watermarking images picture element matrix after conversion;

Step 4, by conversion after medical image picture element matrix in element scan by column, obtain the vector of a line multiple row, this vectorial columns is the number of element in medical image picture element matrix, element in vector is sorted from small to large, and the position of element in former vector in the vector after definite sequence, acquisition primary importance vector, stores primary importance vector as the first key;

Step 5, by conversion after watermarking images picture element matrix in element scan by column, obtain the vector of a line multiple row, this vectorial columns is the number of element in watermarking images picture element matrix, element in vector is sorted from small to large, and the position of element in former vector in the vector after definite sequence, acquisition second place vector, stores second place vector as the second key;

Step 6, determine the position in the vector of element after medical image sequence in the vector after watermarking images sequence, obtain the 3rd position vector, the 3rd position vector is stored as the 3rd key, complete zero watermark embed process;

Step 7, according to the actual requirements, when needs extract watermarking images, pre-service medical image is carried out to matrixing processing, obtain the picture element matrix of this medical image, the line number of this matrix is the line number of image slices vegetarian refreshments, this matrix column number is the columns of image slices vegetarian refreshments, and this entry of a matrix element is the pixel value of pixel;

Step 8, extract stored all keys, the medical image after matrixing is processed carries out real fractional fourier transform, obtains the frequency domain value of each pixel, and then obtains the medical image picture element matrix after conversion;

Step 9, by conversion after medical image picture element matrix in element scan by column, obtain the vector of a line multiple row, this vectorial columns is the number of element in medical image picture element matrix, and the element in vector is sorted according to the first key, obtains the vector after sequence;

Step 10, according to the 3rd key, in the vector after sequence, extract to obtain the vector after watermarking images sequence;

Step 11, according to the second key, the element in vector after watermarking images sequence is carried out to reversed arrangement, and element in the vector after reversed arrangement is reverted to matrix form;

Step 12, the watermarking images matrix after recovering is carried out to real fraction Fourier inverse transformation, obtain the time thresholding of a pixel, the matrix after conversion is original watermark image picture element matrix, completes the extraction to embed watermark image.

2. the medical image based on real fractional fourier transform according to claim 1 zero watermark embedding and extracting method, it is characterized in that, position in vector after definite watermarking images sequence described in step 6 in the vector of element after medical image sequence, if a certain element is not present in the vector after medical image sequence in the vector after watermarking images sequence, the vector after medical image sequence is found with it big or small immediate element position.

3. the medical image based on real fractional Fourier transform according to claim 1 zero watermark embedding and extracting method, it is characterized in that, real fraction Fourier inverse transformation described in step 12, is the real fractional Fourier transform that conversion exponent number value is the opposite number of real fractional Fourier transform conversion exponent number in step 3.