CN104867102A - Method for encrypting medical image robust watermark based on DCT (Discrete Cosine Transform) ciphertext domain - Google Patents

Abstract

The invention relates to a technology for encrypting a medical image watermark based on DCT (Discrete Cosine Transform) and Logistic Map, and belongs to the field of multimedia signal processing. In the steps of the technology, preprocessing of an original medical image and embedding of the watermark are performed firstly. The technology comprises the following steps: (1) acquiring an encrypted image with the DCT and the Logistic Map; (2) performing DCT on the encrypted image, and extracting a feature vector; (3) acquiring a binary logical sequence with the feature vector and a watermark sequence; and performing extraction of the watermark, including: (4) performing DCT on an encrypted medical image to be tested, and extracting one feature vector; (5) extracting the watermark with a Hash function and the binary logical sequence generated during embedding of the watermark; and (6) generating a binary encryption matrix with the Logistic Map to obtain a reduced decrypted medical image. In remote medical treatment, the technology has a high practical value for the protection of personal information of patients.

Description

A kind of encrypted medical image robust watermarking method based on DCT ciphertext domain

Technical field

The invention belongs to field of multimedia signal processing, relate to a kind of medical image digital watermark technology based on dct transform, chaos (Logistic Map) and Image Visual Feature, specifically a kind of chaos encryption medical image robust watermarking method based on DCT ciphertext domain.

Background technology

At present, medical image accounts for 70% ~ 80% of whole hospital medical information, digital content management system has played more and more important effect in modern medical service system, but along with applying of network, add the high speed development of cloud database in recent years, its information security issue comes out gradually.

When medical image carries out remote transmission on network, be recorded in the personal information of the patient on medical picture, easily revealed.If whole medical image is carried out chaos encryption, then using personal information as digital watermark embedding in medical picture, utilize the characteristic of Logistic Map and digital watermarking, we just can be encrypted protection to the medical picture stored beyond the clouds.

Mainly concentrate on spatial domain and transform domain (DCT, DFT and DWT) two aspects to the research in medical image digital watermarking field at present, they carry out embed watermark respectively by the change gray scale of some pixel of spatial domain or the value of some coefficients of transform domain.Wherein cosine transform (Discrete Cosine Transform) territory water mark method, because its calculated amount is less, and with ID compression standard (JPEG, MPEG) compatible, current research many is the focus of existing most frequency field Study of Watermarking.

In view of the singularity requirement protected medical image focal zone, in general document, often select the regions of non-interest (Region of Non-Interest, RONI) watermark information being embedded into image.Area-of-interest (Region of Interest, ROI) in medical image refers to those focal zones comprising important pathological characters or medical information, if at this region embed watermark, then and the diagnosis likely made the mistake.But often people are when finding ROI, spend long time and energy, and once select wrong, then likely disturb the diagnosis of doctor.

Current most digital watermarking is directly added in medical image, but in encrypted medical image, how to embed robust watermarking be still a more insoluble problem, has not yet to see report, still belongs to blank.And under the high speed development of technology beyond the clouds, medical image is often easily revealed, but also is easily subject to conventional attack and geometric attack.

Summary of the invention

The object of this invention is to provide a kind of chaos encryption medical image digital watermark method based on DCT resist geometric attacks, by the visual feature vector by medical image, encryption technology and third-party concept combine, do not need to carry out choosing of area-of-interest, thus solve high in the clouds safety and watermark embedment, the agility problem extracted, there is very desirable robustness and invisibility, with the crypticity of the copyright of conservation medicine image and sufferer information, effectively solve the hiding of patient information and the sensitive question of medical image, solve the resistance geometric attack occurred in medical image applications simultaneously and resist conventional attack problem.

To achieve these goals, the present invention is performed such: first medical image is carried out chaos encryption (Logistic Map), again full figure is carried out dct transform, in dct transform coefficient, extract the medical image visual feature vector of a resist geometric attacks, and common digital watermark and chaos encryption, cryptography, " third party's concept " are combined, achieve anti-geometry and the conventional attack of digital watermarking.The method applied in the present invention comprises the chaos encryption of medical image, watermark embedment, watermark extracting and medical image deciphering four major part, Part I is to original medical image F (i at dct transform domain, j) carry out chaos encryption, comprising: (1) is by initial value x ₀generate chaos sequence, after binary conversion treatment, be expressed as X (j), and X (j) | X (j)=1 ,-1}, preserves x ₀as the key of encrypted medical image.Then overall dct transform is carried out to medical image, then by conversion coefficient and above-mentioned binary chaotic sequence X (j) dot product, then carry out DCT inverse transformation, generate encrypted image C (i, j); Part II is watermark embedment, comprise: (2) are to the medical image C (i after encryption, j) full figure dct transform is carried out, obtain visual feature vector V (j) of encrypted medical image, (3) according to digital watermarking sequence W (j) of stochastic generation and visual feature vector V (j) of image. generate two-valued function sequence Key (j) by Hash function, then two-valued function sequence Key (j) is kept at third party.Part III is watermark extracting, comprise: (4) obtain encrypted medical image C'(i to be measured, j) visual feature vector V ' (j), (5) utilize visual feature vector V ' (j) being present in third-party two-valued function sequence Key (j) and chaos encryption medical image to be measured, utilize Hash Functional Quality to obtain watermark W ' (j).Part IV is the deciphering of encrypted medical image to be measured, comprising: (6) are by the initial value x preserved ₀generating chaos sequence X (j), then by carrying out point multiplication operation in DCT domain, after DCT inverse transformation, obtaining deciphering medical image F'(i, j);

Now be described in detail as follows to method of the present invention:

First by one group of binary pseudo-random that can represent patient information as the watermark that will embed medical image, be designated as W={w (j) | w (j)=0,1; 1≤j≤L}, meanwhile, original medical image, is designated as F={f (i, j) | f (i, j) ∈ R; 1≤i≤N ₁, 1≤j≤N ₂.W (j) and f (i, j) represents the grey scale pixel value of watermark and original medical image respectively, and for the ease of computing, we suppose N ₁=N ₂=N.

Part I: at dct transform domain, chaos encryption is carried out to original medical image F (i, j)

1) generate chaos sequence and obtain chaos encryption medical image C (i, j).

Binary chaotic sequence X (j) is by initial value x ₀generate, and be converted into 1, the two-value series of-1 composition; Preserve x ₀as the key of this medical image of access.Then the original medical image coefficient after binary chaotic sequence X (j) and dct transform is carried out point multiplication operation, then carry out DCT inverse transformation, obtain encrypted image C (i, j).

Part II: the embedding of watermark

2) by carrying out full figure dct transform to encrypted image C (i, j), visual feature vector V (j) of medical image is tried to achieve.

First to encrypted image C (i, j) full figure dct transform is carried out, obtain DCT coefficient Matrix C D (i, j), then at DCT coefficient Matrix C D (i, j) in Low Medium Frequency coefficient, get a front L coefficient, and obtained visual feature vector V (j) of this image by DCT coefficient symbolic operation, specific practice be when DCT coefficient on the occasion of or zero time we represent with " 1 ", represent with " 0 " when coefficient is negative value, program description is as follows:

CD(i,j)＝DCT2(C(i,j))

V(j)＝－Sign(CD(i,j))

3) two-valued function sequence Key (j) is generated according to visual feature vector V (j) of watermark W (j) and image.

$Key\left(j\right)=V\left(j\right)\⊕W\left(j\right)$

Key (j) is by visual feature vector V (j) of encrypted image and watermark W (j) that will embed, and the Hash function conventional by cryptography generates.Preserve Key (j), need to use when extracting watermark afterwards.By being applied for as key to third party by Key (j), to obtain entitlement and the right to use of medical image, thus reach the object of conservation medicine image.

Part III: the extraction of watermark

4) visual feature vector V ' (j) of encrypted image C ' (i, j) to be measured is obtained.

If chaos encryption medical image to be measured is C ' (i, j), after full figure dct transform, obtain DCT coefficient matrix is CD ' (i, j), by the method for above-mentioned Step3, tries to achieve visual feature vector V ' (j) of testing image;

CD’(i,j)＝DCT2(C’(i,j))

V’(j)＝－Sign(CD’(i,j))

5) in encrypted image to be measured, watermark W ' (j) is extracted.

According to visual feature vector V ' (j) of the key K ey (j) generated when embed watermark and encrypted image C ' (i, j) to be measured, utilize Hash function can extract watermark W ' (j) contained by testing image.

$W^{,}\left(j\right)=Key\left(j\right)\⊕V^{,}\left(j\right)$

Part IV: the deciphering of encrypted image C ' (i, j) to be measured

6) generate chaos sequence and obtain deciphering medical image

By the x preserved ₀, obtain chaos sequence X (j) and deciphering medical image C ' (i, j) according to the method for above-mentioned Step1.

The entitlement of testing image and the personal information of patient is differentiated again according to the degree of correlation of W (j) and W ' (j).

The present invention compares with existing medical science digital watermark following advantage:

Watermark can be directly embedded in the medical image of encryption, and there is good robustness.Due to the digital watermark technology that the present invention is the medical image based on DCT and Logistic Map, have computing velocity fast, precision is high, has good compatibility, has stronger resist geometric attacks ability and anti-conventional attack ability; Do not need artificial to carry out choosing of area-of-interest, thus solve the agility problem of watermark embedment; The watermark embedded is a kind of zero watermarking, does not affect original medical image quality, in medical, have very high practical value; Utilize LogisticMap to carry out chaos encryption process to medical image, improve the security of medical image.

Illustrate from theoretical foundation and test figure below:

1) discrete cosine transform (DCT)

DCT is used for the standard that Image Coding is now widely used JPEG compression and MPEG-1/2.DCT is in the little suboptimum orthogonal transformation being only second to Karhunen-Loeve transformation drawn of Minimum Mean Square Error condition, is a kind of harmless chief of a tribe conversion.Its fast operation, precision is high, to extract optimum balance between the ability of characteristic component and arithmetic speed and famous.

2-D discrete cosine direct transform (DCT) formula is as follows:

$\begin{array}{c}F(u,v)=c\left(u\right)c\left(v\right)\underset{x=0}{\overset{M-1}{\Σ}}\underset{y=0}{\overset{N-1}{\Σ}}f(x,y)cos\frac{\mathrm{\π}(2x+1)u}{2M}cos\frac{\mathrm{\π}(2y+1)v}{2N}\\ \begin{array}{cc}u=0,1,\mathrm{...},M-1;& v=0,1,\mathrm{...},N-1;\end{array}\end{array}$

In formula

$\begin{array}{cc}c\left(u\right)=\left\{\begin{array}{cc}\sqrt{1/M}& u=0\\ \sqrt{2/M}& u=1,2,\mathrm{...},M-1\end{array}\right.& ,c\left(v\right)=\end{array}\left\{\begin{array}{cc}\sqrt{1/M}& v=0\\ \sqrt{2/M}& v=1,2,\mathrm{...},N-1\end{array}\right.$

2-D discrete cosine inverse transformation (IDCT) formula is as follows:

$\begin{array}{c}f(x,y)=\underset{u=0}{\overset{M-1}{\Σ}}\underset{v=0}{\overset{N-1}{\Σ}}c\left(u\right)c\left(v\right)F(u,v)cos\frac{\mathrm{\π}(2x+1)u}{2M}cos\frac{\mathrm{\π}(2y+1)v}{2N}\\ \begin{array}{cc}x=0,1,\mathrm{...},M-1;& y=0,1,\mathrm{...},N-1\end{array}\end{array}$

Wherein x, y are spatial domain sampled value; U, v are frequency field sampled value, and usual digital picture pixel square formation represents, i.e. M=N.

2)Logistic Map

Chaos is the similar random process occurred in deterministic system.Had its initial value and parameter, we just can generate this chaos system.Foremost a kind of chaos system is Logistic Map, and recursion formula is as follows:

x _k+1＝μx _k(1-x _k)

Wherein, 0≤μ≤4 are called growth parameter, x _k∈ (0,1) is system variable, and k is iterations.The research work of Chaos dynamic system is pointed out, when growth parameter 3.569945≤μ≤4, Logistic Map works in chaos state.Can see that initial value has a little difference will cause the significant difference of chaos sequence.Therefore, above sequence is a desirable key sequence.Set μ=4 herein, chaos sequence is by different initial value x ₀produce.

3) choosing method of chaos encryption medical image visual feature vector

The main cause of current most of medical image watermarking algorithm resist geometric attacks ability is: people are by digital watermark embedding in pixel or conversion coefficient, and the slight geometric transformation of medical image, usually causes pixel value or transform coefficient values to have larger change.So just, the watermark of embedding can be made under attack very easily.If can find the visual feature vector of reflection medical image geometrical feature, so when little geometric transformation occurs image, can not there is obvious sudden change in the visual characteristic of this image.Hayes research shows that, for characteristics of image, phase place is more important than amplitude.We find through observing the full figure DCT data (Low Medium Frequency) of a large amount of above-mentioned frequency domain encryption images, when carrying out common geometric transformation to an encrypted medical image, some changes may be there are in the size of Low Medium Frequency coefficient, but its coefficient symbols remains unchanged substantially, we choose some experimental datas and are shown in Table 1.The original medical image being used as in table 1 to test is Fig. 1, is the sectioning image (128x128) of the brain of a width chaos encryption.In table, the 1st row display is chaos encryption medical image type under attack, is subject to the medical image after conventional attack and sees Fig. 3-5, be subject to the encrypted medical image after geometric attack and see Fig. 6-9.3rd row, to the 11st row, are CD (1,1)-CD (3,3) 9 the Low Medium Frequency coefficients got in DCT coefficient matrix, and wherein coefficient C (1,1) represents the direct current component value of encrypted medical image.For conventional attack, these Low Medium Frequency coefficient values remain unchanged substantially; For geometric attack, part coefficient has larger change, but we can find, chaos encryption medical image is when being subject to geometric attack, and the size of part DCT Low Medium Frequency coefficient there occurs change but its symbol does not change substantially.Positive DCT coefficient represents with " 1 " by we (containing value is the coefficient of zero), negative coefficient represents with " 0 ", so for encrypted medical image, CD (1 in DCT coefficient matrix, 1)-CD (3, 3) coefficient, corresponding coefficient symbols sequence is: " 110100101 ", in the 12nd row of table 1, we observe these row and can find, no matter conventional attack or this symbol sebolic addressing of geometric attack can keep similar with original chaos encryption medical image, 1.0 (arranging see table 1 the 13rd) are all almost with original chaos encryption medical image normalized correlation coefficient (symbol sebolic addressing length gets 32bit), (conveniently having got 9 DCT coefficient symbols here).

Table 1 chaos encryption medical image full figure dct transform Low Medium Frequency part coefficient and the changing value after attacking by difference

* dct transform coefficient unit 1.0e+003

The related coefficient (vector length 32bit) of table 2 different chaos encrypted medical image feature vector

	V1	V2	V3	V4	V5	V6
							V1	1	0.18	0.07	-0.13	0.38	-0.24
V2	0.18	1	0.27	0.31	0.07	-0.05
							V3	0.07	0.27	1	0.44	0.31	0.06
V4	-0.13	0.31	0.44	1	0.13	0.01
							V5	0.38	0.07	0.31	0.13	1	-0.13
V6	-0.24	-0.05	0.06	0.01	-0.13	1

In order to verify that the coefficient symbols sequence of full figure dct transform is the vision key character belonging to this encryption figure further, we are again different test patterns (see Fig. 1 and Figure 10-14) (see Fig. 2 and Figure 15-19) after dct transform domain chaos encryption, carry out full figure dct transform according to the method described above, obtain corresponding DCT coefficient, F (1,1)-F (4,8), and obtain the related coefficient with the symbol sebolic addressing of former encrypted image, result of calculation is as shown in table 2.

As can be seen from Table 2, between different encrypted medical image, symbol sebolic addressing difference is comparatively large, and the degree of correlation is less, is less than 0.5.

This illustrates that the symbol sebolic addressing of DCT coefficient can reflect the primary visual characteristics of this encrypted medical image more.After the encrypted image containing watermark is by conventional attack to a certain extent and geometric attack, this vector is substantially constant, and this also meets the DCT ability that " has very strong extraction characteristics of image ".According to human vision property (HVS), low intermediate frequency signal is comparatively large to the visual impact of people, represents the principal character of transform domain encrypted medical image.The visual feature vector of the encrypted medical image therefore selected by us is the symbol of Low Medium Frequency coefficient, the number of Low Medium Frequency coefficient select with the size of the original chaos encryption medical image carrying out full figure dct transform and the quantity of information of disposable embedding relevant with the robustness of requirement, L value is less, the quantity of information of disposable embedding is fewer, but robustness is higher.In test below, the length that we choose L is 32bit.

In sum, we, by the analysis to the full figure DCT coefficient of frequency domain encryption image, can utilize the symbol sebolic addressing of Low Medium Frequency coefficient to obtain a kind of method obtaining chaos encryption medical image visual feature vector.

Accompanying drawing explanation

Fig. 1 is original medical image.

Fig. 2 is original encryption medical image.

Fig. 3 is through the image of Gauss's interference.

Fig. 4 is through the image that JPEG attacks.

Fig. 5 is through the image of medium filtering.

Fig. 6 is through the image of rotational transform.

Fig. 7 is through the image of convergent-divergent 0.5 times.

Fig. 8 is through the image of vertical movement.

Fig. 9 is through the image of shear transformation.

Figure 10 is standard testing Fig. 2.

Figure 11 is standard testing Fig. 3.

Figure 12 is standard testing Fig. 4.

Figure 13 is standard testing Fig. 5.

Figure 14 is standard testing Fig. 6.

Figure 15 is the test pattern 2 of Chaotic Scrambling.

Figure 16 is the test pattern 3 of Chaotic Scrambling.

Figure 17 is the test pattern 4 of Chaotic Scrambling.

Figure 18 is the test pattern 5 of Chaotic Scrambling.

Figure 19 is the test pattern 6 of Chaotic Scrambling.

Figure 20 is Chaotic Scrambling image when not disturbing.

The watermark that Figure 21 extracts when being and not disturbing.

Figure 22 is the Chaotic Scrambling (Gauss's interference strength is 15%) when having Gauss to disturb.

Figure 23 is the watermark of extracting when having Gauss to disturb.

Figure 24 is the Chaotic Scrambling image (compression quality is 20%) after JPEG compression.

Figure 25 is the watermark of extracting after JPEG compression.

Figure 26 is the Chaotic Scrambling image (120 filtering through [3 × 3]) after medium filtering.

Figure 27 is the watermark of extracting after medium filtering.

Figure 28 is the Chaotic Scrambling image after rotation 1 degree.

Figure 29 is the watermark of rotation 1 degree of rear extraction.

Figure 30 to be zoom factor be 0.5 Chaotic Scrambling image.

The watermark of Figure 31 to be zoom factor be image zooming-out of 0.5.

Figure 32 is the vertical Chaotic Scrambling image moved after 7%.

Figure 33 is vertical mobile 7% rear watermark of extracting.

Figure 34 is the Chaotic Scrambling image that Y-axis shears after 12%.

Figure 35 is the watermark that Y-axis shears the image zooming-out after 12%.

Embodiment

Below in conjunction with accompanying drawing, the invention will be further described, first by one group of binary pseudo-random that can represent patient information as the watermark that will embed medical image, be designated as W={w (j) | w (j)=0,1; 1≤j≤L}.See Figure 20 by the original medical image after Logistic Map Chaotic Scrambling, can obviously see that medical image has a very large change, security improves.Be designated as: F={f (i, j) | f (i, j) ∈ R; 1≤i≤N1,1≤j≤N2}.Corresponding full figure DCT coefficient matrix is CD (i, j), and getting its Low Medium Frequency coefficient is Y (j), 1≤j≤L, the DC component of first value Y (1) representative image, then frequency order arrangement from low to high.Consider the capacity of robustness and disposable embed watermark, we select the 4x8=32 of a medium and low frequency coefficient to do proper vector, i.e. L=32; The DCT coefficient matrix chosen is CD (i, j), 1≤i≤4,1≤j≤8.After extracting W ' (j) by watermark extraction algorithm, then calculate the normalized correlation coefficient NC of W ' (j) and W (j), judge noly have watermark embedment.

The watermark that Figure 21 extracts when being and not adding interference, can see NC=1.00, the existence of watermark obviously be detected.

We judge anti-conventional attack ability and the resist geometric attacks ability of this digital watermark method by specific experiment below.

First test the ability of the anti-conventional attack of this watermarking algorithm.

(1) Gaussian noise is added

Imnoise () function is used to add gaussian noise in chaos encryption medical image.

Chaos encryption medical image when Figure 22 is Gaussian noise intensity 15% is visually very fuzzy;

Figure 23 is the watermark of extracting, NC=0.77.

Table 3 is watermark anti-Gauss detection data when disturbing.Can see from experimental data, when Gaussian noise intensity up to for 15% time, watermarking images PSNR is down to 10.20dB, and the watermark related coefficient NC=0.77 at this moment extracted, still can detect the existence of watermark.This illustrates the anti-Gaussian noise ability adopting this invention to have.

The anti-Gauusian noise jammer data of table 3 watermark

Noise intensity (%)	1	3	5	7	9	15
							PSNR(dB)	20.05	15.49	13.61	12.35	11.62	10.20
NC	0.89	0.87	0.81	0.81	0.81	0.77

(2) JPEG compression process

Image compression quality percentage is adopted to carry out JPEG compression as parameter to chaos encryption medical image;

Figure 24 to be compression quality be 20% image, there is blocking artifact in this figure;

Figure 25 is the watermark of extracting, and NC=1.00, obviously detects the existence of watermark.

Table 4 is the experimental data of the anti-JPEG compression of watermarking images.When compression quality is 15%, the existence of watermark still can be recorded, NC=0.76.

The experimental data of the anti-JPEG compression of table 4 watermark

Compression quality (%)	15	20	25	30	40	60	80
								PSNR(dB)	26.98	27.8	28.44	28.93	29.65	30.83	33.15
NC	0.76	1.00	0.94	0.87	0.94	1.00	1.00

(3) medium filtering process

Figure 26 is medium filtering parameter is [3x3], and filtering multiplicity is the chaos encryption medical image of 20, and image has occurred fuzzy;

Figure 27 is the watermark of extracting, and NC=0.94, Detection results is obvious.

Table 5 is the anti-medium filtering ability of watermarking images, it can be seen from the table, when medium filtering parameter is [7x7], when filtering multiplicity is 20, still can record the existence of watermark, NC=0.68.

The anti-medium filtering experimental data of table 5 watermark

Watermark resist geometric attacks ability:

(1) rotational transform

Figure 28 is that chaos encryption medical image rotates 1 °, the at this moment PSNR=23.71dB of chaos encryption medical image, and signal to noise ratio (S/N ratio) is lower;

Figure 29 is the watermark of extracting, and the existence of watermark obviously can be detected, NC=0.82.

Table 6 is watermark anti-rotation attack experimental data.Can see that from table NC=0.62, still can detect the existence of watermark when watermarking images rotates-5 °.

Table 6 watermark anti-rotation attacks experimental data

(2) scale transformation

Figure 30 to be zoom factor be 0.5 chaos encryption medical image, at this moment much smaller than former figure of center image;

Figure 31 is the watermark of extracting, and the existence of watermark obviously can be detected, NC=1.00.

Table 7 is the nonshrink attack experimental data of putting of watermark, as can be seen from Table 7 when the zoom factor of chaos encryption medical image little to 0.5 time, related coefficient NC=1, still can record watermark.Illustrate that this invention has stronger anti-zoom capabilities.

Table 7 watermark is nonshrink puts attack experimental data

Zoom factor	0.5	0.8	1.0	1.2	2.0	4.0
							NC	1.00	0.89	1.00	0.94	1.00	1.00

(3) translation transformation

Figure 32 is that chaos encryption medical image vertically moves down 7%, at this moment PSNR=14.01dB, and signal to noise ratio (S/N ratio) is very low;

Figure 33 is the watermark of extracting, and the existence of watermark obviously can be detected, NC=0.79.

Table 8 is that experimental data is attacked in the anti-translation of watermark.Learn when level from table or vertically move 7%, the existence of watermark still can be detected, therefore this digital watermarking having stronger anti-translation attacking ability.

Experimental data is attacked in the anti-translation of table 8 watermark

(4) shear test

Figure 34 is the situation that chaos encryption medical image shears 12%.

Figure 35 is the watermark of extracting, and the existence of watermark obviously can be detected, NC=0.71.

Table 9 is the anti-shearing experimental data of watermark, and from table, data can learn that this algorithm has certain anti-shear ability.

The anti-shearing attack experimental data of table 9 watermark

By above description of test, this watermark embedding method has stronger anti-conventional attack ability and geometric attack ability.(storage) is front has carried out chaos encryption in transmission for original medical image, and security is strengthened, and the embedding of watermark not affecting former chaos encryption medical image, is a kind of zero watermarking.

Claims (1)

1. the encrypted medical image robust watermarking method based on DCT ciphertext domain, it is characterized in that: at dct transform domain, chaos encryption is carried out to medical image, then dct transform is carried out to encrypted medical image, obtain the visual feature vector of encrypted medical image, and original image encryption is combined with digital watermark, achieve resist geometric attacks and the conventional attack of the digital watermarking of encrypted medical image, this digital watermark method is divided into four parts, amounts to six steps:

Part I is carry out chaos encryption at dct transform domain to original medical image F (i, j), comprising: (1) is by initial value x ₀generate chaos sequence, after binary conversion treatment, be expressed as X (j), and X (j) | X (j)=1 ,-1}, preserves x ₀as the key of encrypted medical image.Then overall dct transform is carried out to medical image, then by conversion coefficient and above-mentioned binary chaotic sequence X (j) dot product, then carry out DCT inverse transformation, generate encrypted image C (i, j);

Part II is watermark embedment, comprise: (2) are to the medical image C (i after encryption, j) full figure dct transform is carried out, obtain visual feature vector V (j) of encrypted medical image, (3) according to digital watermarking sequence W (j) of stochastic generation and visual feature vector V (j) of encrypted image. generate two-valued function sequence Key (j) by Hash function, then two-valued function sequence Key (j) is kept at third party;

Part III is watermark extracting, comprise: (4) obtain encrypted medical image C'(i to be measured, j) visual feature vector V ' (j), (5) utilize visual feature vector V ' (j) being present in third-party two-valued function sequence Key (j) and chaos encryption medical image to be measured, utilize Hash Functional Quality to obtain watermark W ' (j);

Part IV is the deciphering of encrypted medical image to be measured, comprising: (6) are by the initial value x preserved ₀generating chaos sequence X (j), then by carrying out point multiplication operation in DCT domain, after DCT inverse transformation, obtaining deciphering medical image F'(i, j).