CN107067359A - Contourlet area image sharing methods based on Brownian movement and DNA encoding - Google Patents
Contourlet area image sharing methods based on Brownian movement and DNA encoding Download PDFInfo
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- CN107067359A CN107067359A CN201610407638.6A CN201610407638A CN107067359A CN 107067359 A CN107067359 A CN 107067359A CN 201610407638 A CN201610407638 A CN 201610407638A CN 107067359 A CN107067359 A CN 107067359A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T1/00—General purpose image data processing
- G06T1/0021—Image watermarking
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2201/00—General purpose image data processing
- G06T2201/005—Image watermarking
- G06T2201/0203—Image watermarking whereby the image with embedded watermark is reverted to the original condition before embedding, e.g. lossless, distortion-free or invertible watermarking
Abstract
Patent of the present invention discloses a kind of Contourlet area image sharing methods based on Brownian movement and DNA encoding, Contourlet decomposition steps including original image, the DNA encoding step of low frequency sub-band coefficient, Brownian movement and Chen Shi hyperchaotic system formation sequence steps, scramble DNA encoding matrix step, the decoding step of DNA encoding Scrambling Matrix, DNA decoding matrixes generate low frequency sub-band scramble coefficient step, low frequency sub-band scramble coefficient generates scramble image step with high-frequency sub-band coefficient, scramble image generates encrypted image step, the Chinese remainder theorem decomposition step and original image recovering step of encrypted image.The part frequency domain that the Contourlet area image sharing methods based on Brownian movement and DNA encoding employ image enters line shuffle, shadow image encrypt simultaneously after has white noise statistical property, original image can be recovered using t therein secondary shadow images, this method is easier storage and transmission relative to other methods, and can guarantee that confidentiality, strong anti-attack ability and the integrality of significance map picture.
Description
Technical field
The present invention relates to a kind of Contourlet area image sharing methods based on Brownian movement and DNA encoding.
Background technology
What community network was information-based now achieves very big development, while also promoting internet and the hair of big data
Exhibition, but simultaneously also along with substantial amounts of information security issue.Over the last couple of decades, privacy sharing has become special
Research direction.Privacy sharing arises primarily at the sharing problem of the digital cipher of early stage.Later, it was applied to various necks
Domain, such as：The control of nuclear weapon in terms of national defense and military, the key of Distributed Calculation be shared and access control of bank portfolio
Aspect.In order to keep secret validity and security, Shamir and Blakley proposed the general of privacy sharing in 1979
Read.
Secret sharing scheme plays an important role in terms of information protection, and the sharing method of Secret Image is in numeral
Safety of image field is also a study hotspot.1994, Naor and Shamir proposed visual cryptography first on Ou Mihui
Learn, the decryption method of its visual cryptography proposed does not need the knowledge of complicated cryptography, but directly utilizes regarding for the mankind
Feel characteristic to overlapping image decryption.Because the method for proposition causes that the Secret Image after recovering is to damage based on xor operation
, therefore the visual quality of the original image finally recovered is not high.Many scholars were goed deep into for changing secret sharing later
Research and improvement.Encrypted image is also what is required for channel capacity in transmitting procedure, so a kind of it is proposed that base
Image sharing method in Contourlet domains, this process employs the sequence tool that Brownian movement and Chen Shi hyperchaotic systems are generated
The features such as having high complexity and strong randomness, the low frequency part in combination with DNA encoding only in Contourlet domains is put
It is random, and last encrypted image is divided into the secondary shadow images of n.It can not then recover according to the shadow image less than threshold value number
Original image, so increases the attack difficulty of attacker, while also prevent the excessively concentration of the authority of manager and cause
Abuse of civil right；If some shadow images in the shadow image of used threshold value number are tampered, it can not recover former
Beginning image, so as to realize the integrated authentication of image；Simultaneously on the basis of security requirement is met, shadow image size
For the 1/n of encrypted image, so that the storage after image encryption is reduced, while can also reach the shared of image.
The content of the invention
The technical problems to be solved by the invention just there is provided a kind of based on Brownian movement and DNA encoding
Contourlet area image sharing methods, are somebody's turn to do the Contourlet area image sharing methods based on Brownian movement and DNA encoding easy
In realizing the storage and transmission of view data after encryption, and it can guarantee that the confidentiality of significance map picture, strong anti-attack ability and complete
Whole property.
The Technical Solving of invention is as follows：
Countourlet area image sharing methods based on Brownian movement and DNA encoding, it is characterised in that：Original image it is low
The DNA encoding steps of frequency sub-band coefficients, low frequency sub-band scramble coefficient generation step, encrypted image generation step, encrypted image
The recovering step of Chinese remainder theorem decomposition step and original image；
The DNA encoding process of the low frequency sub-band coefficient of original image comprises the following steps：
Step 1.1：Original image obtains low frequency sub-band coefficient and high-frequency sub-band coefficient by Contourlet wavelet decompositions；
Step 1.2：Determine Chen Shi hyperchaotic systems and choose initial parameter, generation chaos sequence x1, x2, x3, x4；
Step 1.3：Utilize chaos sequence x1, x2, x3, x4Middle x1Sequence determines the DNA encoding rule of low frequency sub-band coefficient；
Step 2：Low frequency sub-band scramble coefficient generating process comprises the following steps：
Step 2.1：Using monte carlo method simulating two-dimensional Brownian movement, and determine step-length r and two angles under polar coordinates
b,a；
Step 2.2：The position that different matrixes storage Brownian Particles are moved is selected according to the size of image, while by DNA encoding square
Battle array piecemeal processing；
Step 2.3：For DNA encoding matrix, DNA encoding matrix is carried out using the ordering scenario of the Brownian Particles position of generation
Scramble obtains DNA encoding Scrambling Matrix；
Step 2.4：The x generated using Chen Shi hyperchaotic systems4Sequence determines DNA decoding rules, and DNA encoding Scrambling Matrix is given birth to
Into DNA decoding matrixes；
Step 2.5：DNA decoding matrixes are generated into low frequency scramble coefficient matrix, while will using inverse Contourlet wavelet transformations
Low frequency sub-band coefficient generates the scramble image of original image with high-frequency sub-band coefficient；
Step 3：Encrypted image generating process comprises the following steps：
Step 3.1：Bit ex-situ operations by the scramble image of original image Jing Guo pixel；
Step 3.2：Utilize chaos sequence x1, x2, x3, x4Xor operation is carried out with the scramble image after bit ex-situ operations to obtain
To the encrypted image of original image；
Step 4：The Chinese remainder theorem decomposition of encrypted image and the recovery process step of original image comprise the following steps：
Step 4.1：Encrypted image is divided into the secondary shadow images of n using Chinese remainder theorem；
Step 4.2：The secondary shadow images of t in the secondary shadow images of n are chosen, the encryption of original image is obtained using Chinese remainder theorem
Image；
Step 4.3：The sequence x generated using Chen Shi hyperchaotic systems1, x2, x3, x4The encrypted image of original image is compared
Special ex-situ operations obtain the scramble image of original image with xor operation；
Step 4.4：Using Contourlet wavelet transformations by scramble picture breakdown obtain the high-frequency sub-band coefficient of scramble image with
Low frequency sub-band scramble coefficient；
Step 4.5：Utilize the x of Chen Shi hyperchaotic systems4Sequence determines DNA encoding rule and changes into low frequency scramble coefficient
DNA encoding Scrambling Matrix；
Step 4.6：Utilize Chen Shi hyperchaotic systems generation chaos sequence x2With x3, and use monte carlo method simulating two-dimensional cloth
Bright motion, DNA encoding matrix is generated using resulting sequence by DNA encoding Scrambling Matrix；
Step 4.7：The sequence x generated using Chen Shi hyperchaotic systems1The decoding rule of DNA encoding matrix is determined, is decoded
For low frequency sub-band coefficient；
Step 4.8：Low frequency sub-band coefficient and high-frequency sub-band coefficient are generated into original image using Contourlet inverse wavelet transforms.
In step 1.1, decomposed using Contourlet wavelet transformations；Contourlet wavelet transformations are first decomposed into by LP
Low frequency sub-band coefficient and high-frequency sub-band coefficient, wherein low frequency sub-band coefficient be by original image by two-dimensional low-pass filter and every
Row is produced every row down-sampling, and original image subtracts formation high-frequency sub-band coefficient after this low frequency component；High-frequency sub-band coefficient is again
2 are decomposed into by anisotropic filter groupiIndividual directional subband coefficient, image can be realized by repeating said process to low frequency sub-band coefficient
Multi-direction decomposition is differentiated, here using 4n*4m*8 gray level image after the conversion of Contourlet wavelet transformations three-level more
Obtain n*m low frequency sub-band coefficient matrix, four n*m high-frequency sub-band coefficient matrix, four n*2m high-frequency sub-band coefficient square
The high-frequency sub-band coefficient matrix of battle array and four 2n*m, while n*m low frequency sub-band coefficient matrix is changed into n*m*8 binary system
Low frequency sub-band coefficient matrix.
Step 1.2 is carried out as follows：
Step 1.2.1：Determine Chen Shi hyperchaotic systems：
Step 1.2.2：Selecting All Parameters a=36, b=3, c=28, d=-16 and k=0.2 produce four chaos sequence x1, x2, x3,
x4；
Step 1.2.3：Calculate xi=mod ((abs (xi)-floor(abs(xi)))*1014, 256, i=1,2,3,4, wherein abs
() represents to take absolute value, and floor () represents flow in upper plenum, and this four chaos sequences are designated as into x again1, x2, x3,
x4。
Step 1.3 is carried out as follows：
Step 1.3.1：DNA sequence dna formula is made up of four kinds of bases A, T, C, G, and wherein A and T complementations, C and G are complementary；With 00,01,10
Binary coding is carried out to four bases in DNA sequence dna respectively with 11, the coding rule in table 1 is determined.
Table 1DNA coding rules
| Rule 1 | Rule 2 | Rule 3 | Rule 4 | Rule 5 | Rule 6 | Rule 7 | Rule 8 |
| 00-C | 00-C | 00-A | 00-A | 00-T | 00-T | 00-G | 00-G |
| 01-A | 01-T | 01-C | 01-G | 01-C | 01-C | 01-A | 01-A |
| 10-T | 10-A | 10-G | 10-C | 10-G | 10-G | 10-T | 10-T |
| 11-G | 11-G | 11-T | 11-T | 11-A | 11-A | 11-C | 11-C |
Step 1.3.2：To the chaos sequence x generated in step 1.21In last number carry out mod8+1 operation, root
DNA encoding rule is chosen according to result；If the result obtained after mod is 1, then selected DNA encoding rule is exactly rule
1；DNA of the coding as n*m*4 is carried out to the binary system low frequency sub-band coefficient matrix for n*m*8 according to selected coding rule
Encoder matrix.
In step 2.1, using monte carlo method simulating two-dimensional Brownian movement, here using spherical coordinate：X=r
Sin a cos b, Y=r sin a sin b, wherein 0≤r≤+ ∞, 0≤b≤2 π, 0≤a≤π；Step-length r=2 is especially chosen,
Two angles b, a are defined simultaneously and the random direction of motion of Brownian Particles is provided under polar coordinates, then return Descartes's seat
The x of each Brownian Particles position, y-component are calculated in mark system.
In step 2.2, by simulating random motion situation of the Brownian Particles in two-dimensional space, one can be defined
300*2 matrix deposits the position of these Brownian Particles, and wherein first row deposits the position of x-component, secondary series storage y-component
Position (positions for the Brownian Particles that can define different matrixes according to the size of picture to store motion).
Step 2.3 is carried out as follows：
Step 2.3.1：By the DNA encoding matrix that n*m*4 DNA encoding matrix-split is four n*m, using old in step 1.2
X produced by family name's hyperchaotic system2And x3Sequence, makes a=x2* 2 π, b=x3* π, while utilizing Monte-carlo Simulation Blang
Motion produces two sequence x2' and x3', wherein x2'=(x2,1', x2,2' ... x2, n') and x3'=(x3,1', x3,2' ...,
x3, m'), then to x2' and x3' two sequences carry out a liter sequence sort (x respectively2') and sort (x3′)；
Step 2.3.2：For [x2', index2]=sort (x2') and [x3', index3]=sort (x3'), if the position of ascending chain
Put that coordinate index is different from position coordinates original in n*m DNA encoding matrix, need to be by the original in n*m DNA encoding matrix
The value for carrying out the DNA corresponding to position coordinates is replaced to the coordinate position corresponding to index；If the position coordinates in ascending chain
Index is identical with position coordinates original in n*m DNA encoding matrix, then without being replaced；
Step 2.3.3：DNA encoding matrix progress so operation to four pieces of n*m can just generate n*m*4 DNA encoding scramble
Matrix (if image very little, can carry out DNA encoding scramble to image without being divided image with two ascending chains generated
Block processing).
Step 2.3 is carried out as follows：
Step 2.3.1：For the Hyperchaotic Sequence x produced by Chen Shi hyperchaotic systems4In last number carry out mod8+1
Operation；
Step 2.3.2：Result in step 2.3.1 chooses DNA decoding rules, and carrying out DNA to DNA encoding Scrambling Matrix translates
Code generation n*m*8 binary system low frequency sub-band scramble coefficient matrix.
Step 2.4 is carried out as follows：
Step 2.4.1：N*m*8 binary system low frequency sub-band scramble coefficient matrix is changed into n*m low frequency sub-band scramble coefficient
Matrix；
Step 2.4.2：High-frequency sub-band coefficient matrix and n*m low frequency sub-band scramble coefficient matrix is small by inverse Contourlet
Wave conversion obtains the scramble image I of 4n*4m original images.
Step 3.2 is carried out as follows：
Step 3.2.1：Scramble image I changes into unite8 types and is designated as I；
Step 3.2.2：By scramble image I first pixel and chaos sequence x1In first element carry out xor operation obtain
To pixel S ' (1,1), while carrying out bit ex-situ operations to the pixel：1 and 7 exchange, 2 and 5 exchange, 3 and 4 exchange, 6 and 8 pairs
Change, S (1,1) is designated as after exchange；Further, by second pixel and chaos sequence x2In second element carry out it is different
Or operation, and it is obtained into S ' (1,2) with carrying out bit ex-situ operations again after S (1,1) progress xor operations, then by it
It is denoted as S (1,2)；Same processing, which is also done, for the 3rd pixel and the 4th pixel obtains S (1,3) and S (Isosorbide-5-Nitrae)；
Step 3.2.3：Xor operation successively more than is regular, by remaining each pixel and chaos sequence x1, x2, x3, x4
In corresponding element carry out xor operation and obtain S ' (i, j), wherein 1 ＜ i≤256,1 ＜ j≤256, while further by S '
(i, j) carries out xor operation with S ' (i, j-1) and obtains S ' (i, j) again, and finally S ' (i, j) is carried out using bit ex-situ operations
Bit ex-situ operations obtain S (i, j), so can be obtained by the encrypted image of scramble image.
In step 4.1, different Big primes are chosen, the Chinese remainder theorem more than, the encryption figure of low frequency sub-band
As the secondary shadow image S of n can be decomposed into1, S2..., Sn；For 256*256*8 lena gray level images, a is deposited in selection1=241, a2
=247, a3=251, a4=253, threshold value t=3, fourth officer shadow image S can be obtained using Chinese remainder theorem1, S2, S3,
S4。
The present invention is utilized it can be seen from above-mentioned technical scheme Brownian movement and the sequence of Chen Shi hyperchaotic systems generation
The features such as row have high complexity and strong randomness, the low frequency part in combination with DNA encoding only in Contourlet domains is entered
Line shuffle, and last encrypted image is divided into the secondary shadow images of n, and being only collected into could recover no less than the secondary shadow images of t
Former original image, can not recover original image if less than the secondary shadow images of t, so increase the attack difficulty of attacker, together
When also prevent manager authority excessively concentration caused by abuse of civil right；If the shadow image in t pair shadow images meets with
To distorting, then it can not recover original image, so as to realize the integrated authentication of original image, while will meeting security
On the basis of asking, shadow image size is the 1/n of encrypted image, so as to reduce the storage after image encryption and reach encryption figure
Picture it is shared.On the basis of confidentiality and efficiency is met, the utilization rate of hollow of storing process can be improved and be transmitted across
The utilization rate of bandwidth in journey.
Brief description of the drawings
Fig. 1 is the procedure chart of low frequency sub-band coefficient scramble in the present invention.
Fig. 2 is the procedure chart of shadow image generation in the present invention.
Fig. 3 is the recovery process figure of low frequency sub-band coefficient in the present invention.
Fig. 4 is the procedure chart that the original image in the present invention recovers.
Fig. 5 is that original image in the present invention, encrypted image are divided into the recovery figure of several shadow images and original image
Example.(figure (a) represents original image, and figure (b) represents the original image recovered, and (c) -- (f) represents the shadow of original image to figure
Image).
Embodiment is as follows：
Below with reference to accompanying drawing and instantiation, the present invention is described in further detail, but does not limit this hair in any way
Bright scope.The image that image size selected by the present embodiment is 256*256*8, the gray value of image pixel is 0-256
Between integer.
The scrambling process of the low frequency sub-band coefficient of original image specifically includes implemented below step referring to Fig. 1：
Step a. is decomposed using Contourlet wavelet transformations；Contourlet wavelet transformations are first decomposed into low frequency sub-band system by LP
Number and high-frequency sub-band coefficient, wherein low frequency sub-band coefficient are to be adopted by original image by two-dimensional low-pass filter and interlacing every under row
What sample was produced, original image subtracts formation high-frequency sub-band coefficient after this low frequency component；High-frequency sub-band coefficient is filtered by direction again
Ripple device group is decomposed into 2iIndividual directional subband coefficient, repeating said process to low frequency sub-band coefficient can realize that many resolutions of image are multi-party
To decomposition, 64*64 is obtained after the conversion of Contourlet wavelet transformations three-level using 256*256*8 gray level image here
Low frequency sub-band coefficient matrix, four 64*64 high-frequency sub-band coefficient matrix, four 64*128 high-frequency sub-band coefficient matrix and
Four 128*64 high-frequency sub-band coefficient matrix, enters while 64*64 low frequency sub-band coefficient matrix is changed into the two of 64*64*8
Low frequency sub-band coefficient matrix processed；
Step b. determines Chen Shi hyperchaotic systems：
Step c. Selecting All Parameters a=36, b=3, c=28, d=-16, k=0.2 and y0=[0.3, -0.2,1,1.4] produces four
Individual chaos sequence x1, x2, x3, x4；
Step d. calculates xi=mod ((abs (xi)-floor(abs(xi)))*1014, 256, i=1,2,3,4, wherein abs ()
Expression takes absolute value, and floor () represents flow in upper plenum, and this four chaos sequences are designated as into x again1, x2, x3, x4；
Step e. is to chaos sequence x1In last number carry out mod8+1 operation, according to result choose table 1 in DNA compile
Code rule；If the result obtained after mod is 1, then selected DNA encoding rule is exactly rule 1；Compiled according to selected
Code rule carries out DNA encoding matrix of the coding as 64*64*4 to the binary system low frequency sub-band coefficient matrix for 64*64*8；
Step f. utilizes monte carlo method simulating two-dimensional Brownian movement, using spherical coordinate：X=r sin a cos b, Y=r
Sin a sin b, wherein 0≤r≤+ ∞, 0≤b≤2 π, 0≤a≤π；Step-length r=2 is especially chosen, while defining two angles
B, a simultaneously provide the random direction of motion of Brownian Particles under polar coordinates, then return in cartesian coordinate system calculate it is each
The x of Brownian Particles position, y-component；
Step g. can define 300*2 matrix by simulating random motion situation of the Brownian Particles in two-dimensional space
To deposit the position of these Brownian Particles, wherein first row deposits the position of x-component, the position of secondary series storage y-component (according to
The size of picture can define different matrixes come the position for the Brownian Particles for storing motion)；By 64*64*4 DNA encoding square
Battle array is split as four 64*64 DNA encoding matrix, utilizes the x produced by Chen Shi hyperchaotic systems in step 1.22And x3Sequence,
Make a=x2* 2 π, b=x3* π, while utilizing Monte-carlo Simulation Brownian movement to produce two sequence x2' and x3', wherein x2′
=(x2,1', x2,2' ... x2, n') and x3'=(x3,1', x3,2' ..., x3, m'), then to x2' and x3' two sequences are carried out respectively
Rise sequence sort (x2') and sort (x3′)；
Step h. is for [x2', index2]=sort (x2') and [x3', index3]=sort (x3'), if the position of ascending chain is sat
Mark index different from position coordinates original in 64*64 DNA encoding matrix, need to be by the original in 64*64 DNA encoding matrix
The value for carrying out the DNA corresponding to position coordinates is replaced to the coordinate position corresponding to index；If the position coordinates in ascending chain
Index is identical with position coordinates original in 64*64 DNA encoding matrix, then without being replaced；
Step i. carries out so operating the DNA encoding that can just generate 64*64*4 to put to four pieces of 64*64 DNA encoding matrix excessively
Random matrix (if image very little, can carry out DNA encoding scramble to image without being carried out to image with two ascending chains generated
Piecemeal processing)；
Step j. is for the Hyperchaotic Sequence x produced by Chen Shi hyperchaotic systems4In last number carry out mod8+1 behaviour
Make；Result in step 2.3.1 chooses DNA decoding rules, and DNA decoding generations 64* is carried out to DNA encoding Scrambling Matrix
64*8 binary system low frequency sub-band scramble coefficient matrix.
The process of shadow image generation may refer to Fig. 2, specifically include procedure below：
Step a. changes into 64*64*8 binary system low frequency sub-band scramble coefficient matrix n*m low frequency sub-band scramble coefficient square
Battle array；
High-frequency sub-band coefficient matrix and 64*64 low frequency sub-band scramble coefficient matrix are passed through inverse Contourlet small echos by step b.
Conversion obtains the scramble image I of 256*256 original images；And scramble image I is changed into unite8 types and I is designated as；
Step c. is by scramble image I by its first pixel and chaos sequence x1In first element carry out xor operation obtain
Pixel S ' (1,1), while carrying out bit ex-situ operations to the pixel：The exchange of the exchange of the exchange of 1 and 7 exchanges, 2 and 5,3 and 4,6 and 8,
S (1,1) is designated as after exchange；Further, by second pixel and chaos sequence x2In second element carry out XOR
Operation, and it is obtained into S ' (1,2) with carrying out bit ex-situ operations again after S (1,1) progress xor operations, then remembered
Make S (1,2)；Same processing, which is also done, for the 3rd pixel and the 4th pixel obtains S (1,3) and S (Isosorbide-5-Nitrae)；
The xor operation rules of step d. successively more than, by remaining each pixel and chaos sequence x1, x2, x3, x4Middle institute
Corresponding element carries out xor operation and obtains S ' (i, j), wherein 1 ＜ i≤256,1 ＜ j≤256, while further by S ' (i, j)
Carry out xor operation again with S ' (i, j-1) and obtain S ' (i, j), bit finally is carried out to S ' (i, j) using bit ex-situ operations
Ex-situ operations obtain S (i, j), so can be obtained by the encrypted image of scramble image；
Step e. is directed to 256*256*8 lena gray level images, and a is deposited in selection1=241, a2=247, a3=251, a4=253, door
Limit value t=3, fourth officer shadow image S can be obtained using Chinese remainder theorem1, S2, S3, S4.The low frequency sub-band system of original image
Number recovery process may refer to Fig. 3, specifically include procedure below：
Step f chooses three pairs in fourth officer shadow image, and threshold value t=3 here passes through parameter a1=239, a2=249, a3
=251, a4=254 and Chinese remainder theorem obtain encrypted image；
Step g utilizes the chaos sequence x generated in Chen Shi hyperchaotic systems1, x2, x3, x4Simultaneously by encrypted image by its first
Pixel carries out bit ex-situ operations：The exchange of the exchange of the exchange of 1 and 7 exchanges, 2 and 5,3 and 4,6 and 8, so as to obtain S ' (i, j), simultaneously
By its result and chaos sequence x1In first element carry out xor operation, obtain pixel A (1,1)；
Second pixel is carried out obtaining S ' (1,2) after the bit transposition of the above by step h., then with chaos sequence x2In
Two elements carry out xor operation, and resulting result and S (1,1) are carried out obtaining pixel A after xor operation again
(1,2)；The xor operation rule more than, carries out bit change place by remaining each pixel in encrypted image and gets in return successively
To S ' (i, j) wherein 1 ＜ i≤256,1 ＜ j≤256, further by chaos sequence x1, x2, x3, x4In corresponding element and S '
(i, j) carries out xor operation, and it is obtained into A (i, j) with S (i, j) xor operation, so can be obtained by encrypted image
Scramble image；
Step i. obtains 64*64 low frequency sub-band scramble coefficient matrix, four 64*64 height by Contourlet wavelet transformations
The high-frequency sub-band coefficient matrix of frequency sub-band coefficients matrix, four 128*64 high-frequency sub-band coefficient matrix and four 64*128.
The recovery process of original image be may refer into Fig. 4, following process is specifically included：
Step a. changes into the low frequency sub-band scramble coefficient matrix of the 64*64 in Fig. 3 the binary system low frequency that dimension is 64*64*8
Sub-band coefficients matrix；
Decoding rules of the step b. in original scrambling process is as coding rule by 64*64*8 binary system low frequency sub-band
Coefficient matrix be encoded into 64*64*4 DNA encoding Scrambling Matrix；
Step c. simulates random motion situation of the Brownian Particles in two-dimensional space by monte carlo method, by Monte Carlo side
Two sequence x that method simulation Brownian movement is obtained2' and x3' sequence, wherein x2'=(x2,1', x2,2' ... x2, n') and x3'=
(x3,1', x3,2' ..., x3, m'), then to x2' and x3' two sequences carry out a liter sequence sort (x respectively2') and sort (x3′)；
Step d. is to [x2', index2]=sort (x2') and [x3', index3]=sort (x3'), the position after ascending order arrangement
Coordinate is compared with original position coordinates, so that four 64*64 DNA encoding Scrambling Matrix to be converted to 64*64*4 DNA
Encoder matrix；
Step e. chooses original DNA encoding rule as decoding rule and DNA decoding lifes is carried out to 64*64*4 DNA encoding matrix
Into 64*64*8 binary system low frequency sub-band scramble coefficient matrix, while converting it into the low frequency sub-band scramble coefficient for 64*64
Matrix；
Step f. enters line translation to low frequency sub-band coefficient and high-frequency sub-band coefficient using inverse Contourlet wavelet transformations and obtains original
Beginning image.
The shadow image that original image is resolved into may refer to Fig. 5 with the original image recovered, in Figure 5, scheme (a) generation
Table original image, its size is 256*256*8bit.
Figure (c)-(f) represents shadow image resulting after encrypted image is decomposed by Chinese remainder theorem.
Scheme (b) and represent the original image S recovered.
For the coefficient correlation of the adjacent pixel that calculates original image and shadow image.We scheme to original image with encryption
As it is random respectively in the horizontal direction, vertical direction and it is diagonally opposed on have chosen 2500 pairs of adjacent pixels, it is and adjacent to these
Correlation distribution situation between pixel is tested.In table 2, we list original image and shadow image in water
Square to the correlation between, vertical direction and diagonally opposed upper adjacent pixel.We can be found that original image exists from table
There is very strong correlation on three directions, but correlation of four shadow images in three directions is very low.
The correlation of the image pixel value of table 2
Claims (11)
1. the Countourlet area image sharing methods based on Brownian movement and DNA encoding, it is characterised in that：Original image
The DNA encoding step of low frequency sub-band coefficient, low frequency sub-band scramble coefficient generation step, encrypted image generation step, encrypted image
Chinese remainder theorem decomposition step and original image recovering step；
The DNA encoding process of the low frequency sub-band coefficient of original image comprises the following steps：
Step 1.1：Original image obtains low frequency sub-band coefficient and high-frequency sub-band coefficient by Contourlet wavelet decompositions；
Step 1.2：Determine Chen Shi hyperchaotic systems and choose initial parameter, generation chaos sequence x1, x2, x3, x4；
Step 1.3：Utilize chaos sequence x1, x2, x3, x4Middle x1Sequence determines the DNA encoding rule of low frequency sub-band coefficient；
Step 2：Low frequency sub-band scramble coefficient generating process comprises the following steps：
Step 2.1：Using monte carlo method simulating two-dimensional Brownian movement, and determine step-length r and two angles under polar coordinates
b,a；
Step 2.2：The position that different matrixes storage Brownian Particles are moved is selected according to the size of image, while by DNA encoding square
Battle array piecemeal processing；
Step 2.3：For DNA encoding matrix, DNA encoding matrix is carried out using the ordering scenario of the Brownian Particles position of generation
Scramble obtains DNA encoding Scrambling Matrix；
Step 2.4：The x generated using Chen Shi hyperchaotic systems4Sequence determines DNA decoding rules, and DNA encoding Scrambling Matrix is given birth to
Into DNA decoding matrixes；
Step 2.5：DNA decoding matrixes are generated into low frequency scramble coefficient matrix, while will using inverse Contourlet wavelet transformations
Low frequency sub-band coefficient generates the scramble image of original image with high-frequency sub-band coefficient；
Step 3：Encrypted image generating process comprises the following steps：
Step 3.1：Bit ex-situ operations by the scramble image of original image Jing Guo pixel；
Step 3.2：Utilize chaos sequence x1, x2, x3, x4Xor operation is carried out with the scramble image after bit ex-situ operations to obtain
The encrypted image of original image；
Step 4：The Chinese remainder theorem decomposition of encrypted image and the recovery process step of original image comprise the following steps：
Step 4.1：Encrypted image is divided into the secondary shadow images of n using Chinese remainder theorem；
Step 4.2：The secondary shadow images of t in the secondary shadow images of n are chosen, the encryption of original image is obtained using Chinese remainder theorem
Image；
Step 4.3：The sequence x generated using Chen Shi hyperchaotic systems1, x2, x3, x4Bit is carried out to the encrypted image of original image
Ex-situ operations obtain the scramble image of original image with xor operation；
Step 4.4：Using Contourlet wavelet transformations by scramble picture breakdown obtain the high-frequency sub-band coefficient of scramble image with
Low frequency sub-band scramble coefficient；
Step 4.5：Utilize the x of Chen Shi hyperchaotic systems4Sequence determines DNA encoding rule and low frequency scramble coefficient is changed into DNA
Encode Scrambling Matrix；
Step 4.6：Utilize Chen Shi hyperchaotic systems generation chaos sequence x2With x3, and use monte carlo method simulating two-dimensional cloth
Bright motion, DNA encoding matrix is generated using resulting sequence by DNA encoding Scrambling Matrix；
Step 4.7：The sequence x generated using Chen Shi hyperchaotic systems1The decoding rule of DNA encoding matrix is determined, is decoded as
Low frequency sub-band coefficient；
Step 4.8：Low frequency sub-band coefficient and high-frequency sub-band coefficient are generated into original image using Contourlet inverse wavelet transforms.
2. the Contourlet area image sharing methods based on Brownian movement and DNA encoding according to right 1, its feature exists
In：In step 1.1, decomposed using Contourlet wavelet transformations；Contourlet wavelet transformations are first decomposed into low frequency by LP
Sub-band coefficients and high-frequency sub-band coefficient, wherein low frequency sub-band coefficient be by original image by two-dimensional low-pass filter and interlacing every
What row down-sampling was produced, original image subtracts formation high-frequency sub-band coefficient after this low frequency component；High-frequency sub-band coefficient passes through again
Anisotropic filter group is decomposed into 2iIndividual directional subband coefficient, many points of image can be realized by repeating said process to low frequency sub-band coefficient
Multi-direction decomposition is distinguished, is obtained here using 4n*4m*8 gray level image after the conversion of Contourlet wavelet transformations three-level
N*m low frequency sub-band coefficient matrix, four n*m high-frequency sub-band coefficient matrix, four n*2m high-frequency sub-band coefficient matrix and
Four 2n*m high-frequency sub-band coefficient matrix, while n*m low frequency sub-band coefficient matrix to be changed into n*m*8 binary system low frequency
Sub-band coefficients matrix.
3. the Contourlet area image sharing methods according to claim 1 based on Brownian movement and DNA encoding, it is special
Levy and be：Step 1.2 is carried out as follows：
Step 1.2.1：Determine Chen Shi hyperchaotic systems：
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Step 1.2.2：Selecting All Parameters a=36, b=3, c=28, d=-16 and k=0.2 produce four chaos sequence x1, x2, x3, x4；
Step 1.2.3：Calculate xi=mod ((abs (xi)-floor(abs(xi)))*1014, 256), i=1,2,3,4, wherein abs
() represents to take absolute value, and floor () represents flow in upper plenum, and this four chaos sequences are designated as into x again1, x2, x3,
x4。
4. the Contourlet area image sharing methods according to claim 1 based on Brownian movement and DNA encoding, it is special
Levy and be：Step 1.3 is carried out as follows：
Step 1.3.1：DNA sequence dna formula is made up of four kinds of bases A, T, C, G, and wherein A and T complementations, C and G are complementary；With 00,01,10
Binary coding is carried out to four bases in DNA sequence dna respectively with 11, the coding rule in table 1 is determined；
The DNA encoding of table 1 rule
Step 1.3.2：To the chaos sequence x generated in step 1.21In last number carry out mod8+1 operation, according to
As a result DNA encoding rule is chosen；If the result obtained after mod is 1, then selected DNA encoding rule is exactly rule 1；
DNA of the coding as n*m*4 is carried out to the binary system low frequency sub-band coefficient matrix for n*m*8 according to selected coding rule to compile
Code matrix.
5. the Contourlet area image sharing methods according to claim 1 based on Brownian movement and DNA encoding, it is special
Levy and be：In step 2.1, using monte carlo method simulating two-dimensional Brownian movement, here using spherical coordinate：X=
Rsinacosb, Y=r sin a sin b, wherein 0≤r≤+ ∞, 0≤b≤2 π, 0≤a≤π；Step-length r=2 is especially chosen, together
Shi Dingyi two angles b, a simultaneously provide the random direction of motion of Brownian Particles under polar coordinates, then return cartesian coordinate
The x of each Brownian Particles position, y-component are calculated in system.
6. the Contourlet area image sharing methods according to claim 1 based on Brownian movement and DNA encoding, it is special
Levy and be：In step 2.2, by simulating random motion situation of the Brownian Particles in two-dimensional space, one can be defined
300*2 matrix deposits the position of these Brownian Particles, and wherein first row deposits the position of x-component, secondary series storage y-component
Position (positions for the Brownian Particles that can define different matrixes according to the size of picture to store motion).
7. the Contourlet area image sharing methods according to claim 1 based on Brownian movement and DNA encoding, it is special
Levy and be：Step 2.3 is carried out as follows：
Step 2.3.1：By the DNA encoding matrix that n*m*4 DNA encoding matrix-split is four n*m, using old in step 1.2
X produced by family name's hyperchaotic system2And x3Sequence, makes a=x2* 2 π, b=x3* π, while utilizing Monte-carlo Simulation Blang
Motion produces two sequence x2' and x3', wherein x2'=(x2,1', x2,2' ... x2, n') and x3'=(x3,1', x3,2' ..., x3, m),
Then to x2' and x3' two sequences carry out a liter sequence sort (x respectively2') and sort (x3′)；
Step 2.3.2：For [x2', index2]=sort (x2') and [x3', index3]=sort (x3'), if the position of ascending chain
Put that coordinate index is different from position coordinates original in n*m DNA encoding matrix, need to be by the original in n*m DNA encoding matrix
The value for carrying out the DNA corresponding to position coordinates is replaced to the coordinate position corresponding to index；If the position coordinates in ascending chain
Index is identical with position coordinates original in n*m DNA encoding matrix, then without being replaced；
Step 2.3.3：DNA encoding matrix progress so operation to four pieces of n*m can just generate n*m*4 DNA encoding scramble
Matrix (if image very little, can carry out DNA encoding scramble to image without being divided image with two ascending chains generated
Block processing).
8. the Contourlet area image sharing methods according to claim 1 based on Brownian movement and DNA encoding, it is special
Levy and be：Step 2.3 is carried out as follows：
Step 2.3.1：For the Hyperchaotic Sequence x produced by Chen Shi hyperchaotic systems4In last number carry out mod8+1
Operation；
Step 2.3.2：Result in step 2.3.1 chooses DNA decoding rules, and carrying out DNA to DNA encoding Scrambling Matrix translates
Code generation n*m*8 binary system low frequency sub-band scramble coefficient matrix.
9. the Contourlet area image sharing methods according to claim 1 based on Brownian movement and DNA encoding, it is special
Levy and be：Step 2.4 is carried out as follows：
Step 2.4.1：N*m*8 binary system low frequency sub-band scramble coefficient matrix is changed into n*m low frequency sub-band scramble coefficient
Matrix；
Step 2.4.2：High-frequency sub-band coefficient matrix and n*m low frequency sub-band scramble coefficient matrix is small by inverse Contourlet
Wave conversion obtains the scramble image I of 4n*4m original images.
10. the Contourlet area image sharing methods according to claim 1 based on Brownian movement and DNA encoding, its
It is characterised by：Step 3.2 is carried out as follows：
Step 3.2.1：Scramble image I changes into unite8 types and is designated as I；
Step 3.2.2：By scramble image I first pixel and chaos sequence x1In first element carry out xor operation obtain
To pixel S ' (1,1), while carrying out bit ex-situ operations to the pixel：1 and 7 exchange, 2 and 5 exchange, 3 and 4 exchange, 6 and 8 pairs
Change, S (1,1) is designated as after exchange；Further, by second pixel and chaos sequence x2In second element carry out it is different
Or operation, and it is obtained into S ' (1,2) with carrying out bit ex-situ operations again after S (1,1) progress xor operations, then by it
It is denoted as S (1,2)；Same processing, which is also done, for the 3rd pixel and the 4th pixel obtains S (1,3) and S (Isosorbide-5-Nitrae)；
Step 3.2.3：Xor operation successively more than is regular, by remaining each pixel and chaos sequence x1, x2, x3, x4
In corresponding element carry out xor operation and obtain S ' (i, j), wherein 1 ＜ i≤256,1 ＜ j≤256, while further by S '
(i, j) carries out xor operation with S ' (i, j-1) and obtains S ' (i, j) again, and finally S ' (i, j) is carried out using bit ex-situ operations
Bit ex-situ operations obtain S (i, j), so can be obtained by the encrypted image of scramble image.
11. the Contourlet area image sharing methods according to claim 1 based on Brownian movement and DNA encoding, its
It is characterised by：In step 4.1, different Big primes are chosen, the Chinese remainder theorem more than, the encryption figure of low frequency sub-band
As the secondary shadow image S of n can be decomposed into1, S2..., Sn；For 256*256*8 lena gray level images, a is deposited in selection1=241, a2
=247, a3=251, a4=253, threshold value t=3, fourth officer shadow image S can be obtained using Chinese remainder theorem1, S2, S3,
S4。
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109214972A (en) * | 2018-08-16 | 2019-01-15 | 电子科技大学 | A kind of image encryption method based on chaos pseudo random DNA enhancing |
| CN109803148A (en) * | 2019-03-13 | 2019-05-24 | 苏州泓迅生物科技股份有限公司 | A kind of image encoding method, coding/decoding method, encoding apparatus and decoding apparatus |
| CN110113618A (en) * | 2019-06-11 | 2019-08-09 | 苏州泓迅生物科技股份有限公司 | A kind of image storage method, read method, storage device and reading device |
| CN110113505A (en) * | 2019-04-24 | 2019-08-09 | 湖北工业大学 | A kind of safe steganography coding method of low disturbance information based on Chinese remainder theorem |
| CN110289083A (en) * | 2019-06-26 | 2019-09-27 | 苏州泓迅生物科技股份有限公司 | A kind of image reconstructing method and device |
| CN111243378A (en) * | 2020-03-17 | 2020-06-05 | 广东智媒云图科技股份有限公司 | Drawing method and device based on fractal Brown motion model |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020097900A1 (en) * | 2000-08-25 | 2002-07-25 | Stmicroelectronics S.R.1. | System for the automatic analysis of images such as DNA microarray images |
| WO2009011735A1 (en) * | 2007-07-16 | 2009-01-22 | Exxonmobil Upstream Research Company | Geologic features from curvelet based seismic attributes |
| CN101445826A (en) * | 2008-06-19 | 2009-06-03 | 新疆农业科学院核技术生物技术研究所 | Simple and new method for identifying copy numbers of transgenic plants |
| CN101540047A (en) * | 2009-04-30 | 2009-09-23 | 西安电子科技大学 | Texture image segmentation method based on independent Gaussian hybrid model |
| US20120081114A1 (en) * | 2009-05-27 | 2012-04-05 | Daniel Weller | System for Accelerated MR Image Reconstruction |
| CN103366337A (en) * | 2013-08-06 | 2013-10-23 | 山东大学 | Digital watermarking method capable of being applied to 2D-3D (Two Dimensional-Three Dimensional) conversion |
| WO2015106373A1 (en) * | 2014-01-17 | 2015-07-23 | 首都医科大学 | Method for establishing prediction model based on multidimensional texture of brain nuclear magnetic resonance images |
| CN105372707A (en) * | 2014-08-27 | 2016-03-02 | 中国石油化工股份有限公司 | Method for attenuating multi-scale seismic data random noise |
-
2016
- 2016-06-08 CN CN201610407638.6A patent/CN107067359A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020097900A1 (en) * | 2000-08-25 | 2002-07-25 | Stmicroelectronics S.R.1. | System for the automatic analysis of images such as DNA microarray images |
| WO2009011735A1 (en) * | 2007-07-16 | 2009-01-22 | Exxonmobil Upstream Research Company | Geologic features from curvelet based seismic attributes |
| CN101445826A (en) * | 2008-06-19 | 2009-06-03 | 新疆农业科学院核技术生物技术研究所 | Simple and new method for identifying copy numbers of transgenic plants |
| CN101540047A (en) * | 2009-04-30 | 2009-09-23 | 西安电子科技大学 | Texture image segmentation method based on independent Gaussian hybrid model |
| US20120081114A1 (en) * | 2009-05-27 | 2012-04-05 | Daniel Weller | System for Accelerated MR Image Reconstruction |
| CN103366337A (en) * | 2013-08-06 | 2013-10-23 | 山东大学 | Digital watermarking method capable of being applied to 2D-3D (Two Dimensional-Three Dimensional) conversion |
| WO2015106373A1 (en) * | 2014-01-17 | 2015-07-23 | 首都医科大学 | Method for establishing prediction model based on multidimensional texture of brain nuclear magnetic resonance images |
| CN105372707A (en) * | 2014-08-27 | 2016-03-02 | 中国石油化工股份有限公司 | Method for attenuating multi-scale seismic data random noise |
Non-Patent Citations (2)
| Title |
|---|
| 吴一全等: "基于Contourlet域Krawtchouk矩和改进粒子群的遥感图像匹配", 《宇航学报》 * |
| 崔瑜等: "基于混沌遗传算法和contourlet变换的医学图像融合", 《第四军医大学学报》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109214972A (en) * | 2018-08-16 | 2019-01-15 | 电子科技大学 | A kind of image encryption method based on chaos pseudo random DNA enhancing |
| CN109214972B (en) * | 2018-08-16 | 2020-04-14 | 电子科技大学 | Image encryption method based on chaos pseudorandom DNA enhancement |
| CN109803148A (en) * | 2019-03-13 | 2019-05-24 | 苏州泓迅生物科技股份有限公司 | A kind of image encoding method, coding/decoding method, encoding apparatus and decoding apparatus |
| WO2020181803A1 (en) * | 2019-03-13 | 2020-09-17 | 苏州泓迅生物科技股份有限公司 | Image encoding method and image decoding method, and encoding apparatus and decoding apparatus |
| CN110113505A (en) * | 2019-04-24 | 2019-08-09 | 湖北工业大学 | A kind of safe steganography coding method of low disturbance information based on Chinese remainder theorem |
| CN110113618A (en) * | 2019-06-11 | 2019-08-09 | 苏州泓迅生物科技股份有限公司 | A kind of image storage method, read method, storage device and reading device |
| WO2020248488A1 (en) * | 2019-06-11 | 2020-12-17 | 苏州泓迅生物科技股份有限公司 | Image storage method, image reading method, image storage device, and image reading device |
| CN110113618B (en) * | 2019-06-11 | 2021-09-03 | 苏州泓迅生物科技股份有限公司 | Image storage method, reading method, storage device and reading device |
| CN110289083A (en) * | 2019-06-26 | 2019-09-27 | 苏州泓迅生物科技股份有限公司 | A kind of image reconstructing method and device |
| CN111243378A (en) * | 2020-03-17 | 2020-06-05 | 广东智媒云图科技股份有限公司 | Drawing method and device based on fractal Brown motion model |
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