CN108537716A - A kind of color image encryption embedding grammar based on discrete domain - Google Patents
A kind of color image encryption embedding grammar based on discrete domain Download PDFInfo
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- CN108537716A CN108537716A CN201810068639.1A CN201810068639A CN108537716A CN 108537716 A CN108537716 A CN 108537716A CN 201810068639 A CN201810068639 A CN 201810068639A CN 108537716 A CN108537716 A CN 108537716A
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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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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/001—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using chaotic signals
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
- H04N1/32—Circuits or arrangements for control or supervision between transmitter and receiver or between image input and image output device, e.g. between a still-image camera and its memory or between a still-image camera and a printer device
- H04N1/32101—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title
- H04N1/32144—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title embedded in the image data, i.e. enclosed or integrated in the image, e.g. watermark, super-imposed logo or stamp
- H04N1/32149—Methods relating to embedding, encoding, decoding, detection or retrieval operations
- H04N1/32267—Methods relating to embedding, encoding, decoding, detection or retrieval operations combined with processing of the image
- H04N1/32272—Encryption or ciphering
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Abstract
The invention discloses a kind of color image encryption embedding grammar based on discrete domain, is related to digital image processing techniques.Secret Image characteristic coefficient is introduced into Logistic chaotic maps and Rabinovich hyperchaotic maps, keeps the sequence of generation related to close figure；The RGB sequences that image is reset using the Logistic chaos sequences of generation, eliminate the color information of coloured image；One group of sequential encryption image pixel positions in the four groups of chaos sequences generated using Rabinovich hyperchaotic maps, using the method for piecemeal scramble, quick encrypted image；Using remaining three groups of Rabinovich Hyperchaotic Sequences subchannels by after image wavelet transform (DWT) low frequency coefficient scramble with diffusion；Encrypted image is embedded into the DWT high frequency coefficients of public image using least significant bit replacement algorithm (LSB).The present invention can be on the basis of protecting picture material safety, the existence of effective protection image information, ensures safety of the image in communication process.
Description
Technical field
The present invention relates to digital image security fields, more particularly to color digital image encryption and hidden method.
Background technology
Currently, important tool of the multimedia as information interchange, a large amount of digital picture is with Internet, wireless network
To propagate, greatly facilitating the access of information and sharing in the Open Network of representative.At the same time, many Sensitive Domains, such as
Commercially, transmission of the image information of scientific research, military and political etc. under open network environment be there is huge security risk,
Include that the illegal of information is obtained, distorted etc. and lead to serious consequence often by various potential artificial attacks, because
This, protects the safety of image information most important.Image information is protected mainly have two aspect, when to image information into
Row encryption, thereby protects the crypticity of image, second is that image information is hidden in another width public image, thereby protects figure
The existence of picture.
American scholar Jessica Fridrich have been put forward for the first time a kind of general image encryption framework：Image pixel is set
Disorderly with diffusion, secure encryption system is realized with this.The position of each pixel is with a kind of puppet first in image scrambling, that is, image
Random manner is disturbed, but pixel value is constant；Then image diffusion is then that pixel position is constant, and pixel value changes.Scramble
It is combined with diffusion, to ensure that encryption system is effective against attack.The image encryption that develops into of chaology carries in recent years
A completely new thinking is supplied.Initial value and systematic parameter extreme sensitivity, ergodic, the track having due to chaos system can not
The series of characteristics such as predictive and good randomness, make it largely be applied to encryption system.Currently, the figure based on chaos
As Encryption Algorithm has become mainstream technology and research hotspot, there is great application prospect.
Image concealing technology utilizes the masking characteristics of redundancy and human vision existing for image itself to image,
Secret Image information can be embedded into public image and be transmitted.In recent years, the research based on image concealing algorithm
It has made great progress, according to the realization method of hidden algorithm, the methods of spatial domain, transform domain, compression domain can be divided into.Compared to sky
For the robustness of domain information concealing technology is poor, the Information Hiding Techniques based on transform domain then do positive alternation to carrier information number
After changing, using human body to the feeling redundancy of frequency domain data, secret data is embedded in hidden frequency domain, is had stronger
Robustness and safety.
The study found that in the prior art, there are key space deficiency, sequence complexities for single, low dimensional chaotic maps
Not high disadvantage, meanwhile, if encrypted image is directly propagated in open channel, it is easy to be attacked due to its not differentiability
The person of hitting perceives.
Invention content
In view of the above problems, the present invention designs a kind of color image encryption embedding grammar based on discrete domain.This method will
Image encryption is combined with image concealing, and the chaos sequence generated using dual chaos system carrys out scramble Secret Image pixel
Position and the domains diffusion image DWT low frequency coefficient, to encrypted image；It then, will in the case where influencing minimum to public image
Encrypted image is embedded into the high frequency coefficient of public image, it is concealed encrypted after image information, so that image is safely existed
It is transmitted in open channel.
1. a kind of color image encryption embedding grammar based on discrete domain of the present invention, includes the following steps：One kind is based on
The color image encryption embedding grammar of discrete domain, includes the following steps：Step 101：Secret Image characteristic coefficient is introduced into logic
In this base of a fruit Logistic chaotic maps and Lapie's Milunovich Rabinovich hyperchaotic maps, generate relevant mixed with Secret Image
Ignorant sequence；Step 102：Using the RGB sequences for each pixel of sequence reorganization image that Logistic chaotic maps generate, eliminate
The color information of coloured image；Step 103：One group in the four groups of chaos sequences generated using Rabinovich hyperchaotic maps
Sequence piecemeal scramble image pixel positions；Step 104：Utilize sequence scramble in remaining three groups of Rabinovich Hyperchaotic Sequences
Secret Image pixel position and the domains diffusion image wavelet transform DWT low frequency coefficient, obtain encrypted image；Step 105：It will
Encrypted image is embedded into the high frequency coefficient after public image DWT transformation, concealed encrypted image information.
Preferably, the step 101 specifically includes：The average value for calculating the secret each channels coloured image RGB, will be averaged
It is worth weighted sum and obtains impact factor Δ, impact factor is added in Logistic chaotic maps and Rabinovich hyperchaotic maps
Initial value on, generate with the relevant chaos sequence of Secret Image.Shown in calculation formula such as formula (1-3)：
E'=0.16 × ER+0.50×EG+0.34×EB (2)
△=E' × 10-10 (3)
Wherein xiIndicate that the pixel value of each channel image pixel, E (x) are average value, E' is that (weights are solid for weighted average
It is fixed), ER、EG、EBRespectively indicate R, G, channel B average pixel value, impact factor △ is obtained after weighted average is reduced, make
For the key of image decryption.
Since chaos system has strong sensibility and dependence to system initial value and parameter, need to will only influence because
Son is added on the initial value of Logistic chaotic maps and Rabinovich hyperchaotic maps, you can generates stable and secret figure
As relevant chaos sequence, including one group of Logistic chaos sequence and four groups of Rabinovich Hyperchaotic Sequences.
Logistic chaotic maps are a kind of common Chaos dynamic systems, have 3 kinds of forms, but full mapping range is small,
Cause numerical value change rate in iterative process small, and uniform distribution properties are not good enough.Therefore the present invention is using a kind of improved
Logistic chaotic maps, as shown in formula (4), full mapping range is xn∈[-2β,2β]。
Wherein, xnIt is respectively state variable and control parameter, x with βnIndicate nth iteration value, initial value x0With factor beta
As key, set by encipherer；When β ∈ (0, ∞), logistc mappings are in chaos state.(in order to make logistc reflect
It penetrates well into chaos state, needs pre- iteration Logistic chaotic maps N0It is secondary, generally take N0≥200).If generating
Logistic chaos sequences are L1。
Rabinovich hyperchaotic map definitions are as follows：
Wherein x, y, z, w indicate the state variable of Rabinovich hyperchaotic maps,Similarly
(wherein d indicates differential, and t is the time)；A, b, d, k, c are system control parameters.Work as a=4, b=-0.5, d=1, k=8.1, c
When=- 2.2, the solution of chaotic maps formula shown in formula (5) is in chaos state, calculate the mapping maximum Lyapunov exponent
(an important quantitative target for weighing system dynamics) is more than zero, and there are two positive Lyapunov values, and
Lyapunov dimensions are not integers, are thus judged, system is in chaos state.Using Fourth order Runge-Kutta to equation (5) into
Row solve, each state variable x, y, z, w initial value as key, set by encipherer.Pre- iteration N0Secondary, every group of sequence is from N0+
1 sequential value starts value.If the Rabinovch Hyperchaotic Sequences generated are R1、R2、R3、R4。
Preferably, the step 102 specifically includes：It is respectively m, n that the line number of picture element matrix and columns are read from image I
Secret coloured image Im×n, it is the Logistic chaos sequences L of m × n to take length1Quantified, make sequential value be distributed in [0,
1] in range, it is then converted into Lm×nMatrix, and corresponded with the pixel of image I.Using each Logistic sequential values as
Criterion, its corresponding pixel points of scramble RGB sequence, can be obtained 6 kinds of sortords, respectively RBG, GRB, GBR, BRG,
BGR、RGB.Scrambling process is as follows：
Step 1：Read in Logistic chaos sequence matrix Lsm×nWith coloured image Im×n,；
Step 2：According to matrix Lm×nIn each element value l replace the RGB sequences of the pixel corresponding to it：When 0≤l≤
When 1/6, the G of pixel, the value of channel B are exchanged, RGB is sequentially converted into RBG；When 1/6<When l≤1/3, the RGB sequences of pixel
Be converted to GRB；When 1/3<When l≤1/2, the RGB of pixel is sequentially converted into GBR；When 1/2<When l≤2/3, the RGB of pixel
It is sequentially converted into BRG；When 2/3<When l≤5/6, the RGB of pixel is sequentially converted into BGR；When 5/6<When l≤1, pixel
RGB sequences are constant.Image I obtains image I after above-mentioned processing1。
Preferably, the step 103 further comprises：4 groups of chaos sequences for selecting Rabinovich chaos systems to generate
In 1 group of chaos sequence R1To image I1Pixel position into line shuffle.In order to improve encryption efficiency, using piecemeal scramble
Image is carried out repeatedly different size of piecemeal and handled by method, and scramble intersects progress between scramble and block in block.Three kinds of setting
Level image piecemeal size：Minimum sub-block min, medium sub-block mid and maximum sub-block max, wherein requiring max that can be divided exactly by min；
By image I1Expansion is done to handle to obtain image I'm'×n'(m' >=m, n' >=n) so that m' and n' can be divided exactly by min, mid and max.
Step 1：Processing in smallest blocks block.By image I1It, will be in each minimum sub-block after minimum sub-block min piecemeals
Pixel does 180 ° of rotations and obtains image I1'；
Step 2：Scramble between largest block block.Image I1' by maximum sub-block size max piecemeals and number, often row and each column
Block number is respectively rmax、cmax；Take rmax×cmaxThe Rabinovich Hyperchaotic Sequences of length, sequence obtain index sequence In, then
It is corresponding with the image block after piecemeal, new numbers of the In as piecemeal, and image block is numbered from small to large sequentially again according to new
Arrangement；
Step 3：Scramble in largest block block.Take first image block after being rearranged in step 2 by min piecemeals, ranks
Block number is rm、cm, separately take rm×cmA Rabinovich Hyperchaotic Sequences, and by this rm×cmA piecemeal sequence scramble.To step 2
In remaining each maximum piecemeal repeat aforesaid operations, until, all by scramble, obtaining image I in all largest block blocks1”；
Step 4：Scramble between medium sub-block block.By image I1" mid piecemeals are pressed, ranks block number is rmid、cmid, separately take rmid×
cmidA Rabinovich Hyperchaotic Sequences are by its scramble.
That is image I1I is obtained after being handled in smallest blocks1', by I1' make to obtain I with scramble in block between maximum piecemeal block1",
Continue I1" make to obtain image I after scramble between medium piecemeal block2。
Preferably, the step 104 uses its excess-three group Rabinovich Hyperchaotic Sequence subchannel scramble and scatter diagram
As the low frequency coefficient after DWT transformation includes：
Using Haar wavelet basis, low frequency component, the level of image will can be obtained after image progress level-one wavelet transformation Haar
Component, vertical component and diagonal components, coefficient matrix are respectively LL, HL, LH, HH (wherein matrix size is m'/2 × n'/2).
Wherein HL, LH, HH are high fdrequency component coefficient matrix, contain the detailed information of image, and low frequency coefficient matrix L L maintains original
The general picture and spatial character of image have concentrated most of energy of image.Abundant experimental results show to set in low frequency coefficient matrix
Disorderly encryption can effectively avoid information leakage and improve safety.
Step 1：By image I2RGB triple channels separation, and respectively carry out DWT transformation, obtain each channel factor matrix L L,
And it is the one-dimension arrays of m'/2 × n'/2 LL to be converted into length.Sequence R is reflected using remaining 3 Rabinovich hyperchaos2、R3、R4
It is corresponding with each channel, sort by size to obtain its index sequence IniAfter (i=2,3,4), respectively with each channel low frequency of image R, G, B
The one-dimension array LL that coefficient matrix is converted into is corresponding, by IniThe new serial number of (i=2,3,4) as each channel LL, is arranged again
Sequence obtains the new coefficient LL' in each channel of position scramble.
Step 2：To R2、R3、R4Sequence is made following formula such as and is handled：
Ri'=mod (floor (1000*abs (Ri),MaxLL), (i=2,3,4) (6)
Wherein mod (a, b) indicates a to b division complementations, and floor indicates that downward rounding, abs expressions take absolute value, MaxLLTable
Show the integer part of maximum value in low frequency coefficient.
By pretreated three groups of sequence R' with respectively with the integer part exclusive or of each channel factor LL' after scramble and protect
It is constant to hold fractional part, is converted into matrix, then obtains final scramble and the low frequency coefficient matrix L L " after diffusion.Carry out inverse transformation
Merge triple channel image afterwards and obtains final encrypted image I3。
Preferably, encrypted image is embedded into public image by the step 105 using least significant bit scrambling algorithm
DWT transformation after high frequency coefficient include：
Discrete wavelet transformer changes commanders the high frequency section of picture signal and low frequency part separates, and the two parts include
Different information.The approximate information of image is included in low frequency component, and the information at edge is included in high fdrequency component.Human eye pair
The perception of marginal information variation is poor, therefore (embedded Secret Image) can be modulated to the high fdrequency component of public image.And
In order to reduce the influence to public image visual quality, the present invention is embedding to the least significant bit of each pixel pixel value of public image
The maximal bit digit entered is 4.
The high frequency section and low frequency part of wavelet transform separating image signals choose the coloured image that size is N × N
C is as carrier image IC, by carrier image ICThe isolated each channel data I of triple channelCr、ICg、ICb, respectively by data ICr、
ICg、ICbThe high frequency coefficient matrix that wavelet transformation obtains twice is carried out, second of wavelet transformation is done again to the high frequency coefficient matrix and is obtained
The coefficient matrix of each high frequency coefficient matrix, by encrypted image I3Each channel data Ir、Ig、IbIt is embedded into image C corresponding channels
Data ICr、ICg、ICbIn.Illustrate image embedding grammar below for the channels R, G, channel B are similarly.Use Haar small first
Wave basic function, by ICrCarry out wavelet transform twice：First time wavelet transformation obtains low frequency coefficient Matrix C A (LL) and high frequency system
Matrix number CH (HL), CV (LH), CD (HH)；Each high frequency coefficient is obtained after doing second of wavelet transformation to three high frequency coefficient matrixes
The coefficient matrix (the two level wavelet conversion coefficient matrix of such as CD coefficient matrixes is CDA, CDH, CDV, CDD) of matrix, totally 12.Add
Close image data will be embedded into the high fdrequency component of second level wavelet conversion coefficient, can at most there is 9 two level high frequency coefficient matrixes
It can use.Embedded step is as follows：
Step 1：By IrIt is converted to binary message code stream (length M)；
Step 2：CDD coefficient matrixes (size is N' × N', N'=N/4) are converted to one-dimensional vector (V), then by Ir's
Binary message code stream is embedded into vectorial V, and embedding grammar is as follows：
If a. M≤2 × N' × N', 2 least significant bits of element in each V are replaced with 2 binary message code streams
(LSB), new one-dimensional vector (V') is obtained；
If b. 2 × N' × N'<M≤3 × N' × N' then replace 3 of element in each V with 3 binary message code streams
LSB obtains V'；
C. 4 LSB that element in each V is otherwise replaced with 4 binary message code streams, obtain V'；
D. the vector (V') obtained after embedding information is converted back into two-dimensional matrix CDD', is substituted into original old coefficient matrix
The position of CDD；
Step 3：If information code current has been not embedded into previous step, successively in coefficient matrix：CDH、CDV、CHD、
Step 2 is repeated in CVD, CHH, CHV, CVH, CVV and is embedded in remaining information code stream, is completed until information code current is embedded in.So far, it obtains
Each coefficient matrix after modulation.
Step 4：DWT transformation is carried out to coefficient matrix CDA.By the coefficient matrix number used in above step and last embedding
Enter the number of bits used in the coefficient matrix of information, is embedded into third level coefficient CDAD, then inverse transformation obtains CDA'.
After the completion of telescopiny, after coefficients at different levels are taken turns doing wavelet transform inverse transformation (IDWT), it is embedding to obtain the channels R
Enter the image of completion.After making same treatment to G, channel B, merges the image in embedded tri- channels R, G, B completed, then obtain embedding
The public image I of the close figure of encryption is enteredC'。
The beneficial effects of the present invention are：It is insufficient to solve simple Chaotic Encryption System key space, sequence complexity is not
High problem, and encrypted image information is concealed, enable image safe transmission in open channel.
Description of the drawings
Fig. 1 is the color image encryption embedded mobile GIS flow chart the present invention is based on discrete domain；
Fig. 2 is image encryption partial process view of the present invention；
Fig. 3 is DWT transformation schematic diagrames；
Fig. 4 a artwork R channel images；
R channel images after Fig. 4 b RGB sequence scrambles；
Fig. 5 a image RGB sequences scramble experimental result pictures of the present invention；
Fig. 5 b image block scramble experimental result pictures of the present invention；
Fig. 5 c low frequency coefficient scramble experimental result pictures of the present invention；
The image lena artworks that Fig. 5 d present invention tests；
The correct decrypted image of Fig. 5 e present invention；
The wrong decrypted image of Fig. 5 f present invention；
Image and image histogram analysis comparison diagram after encryption before Fig. 6 present invention encryption；
The channels the R correlation comparison diagram of image before and after Fig. 7 image encryptions of the present invention；
Fig. 8 public image DWT coefficient matrixes of the present invention are embedded in schematic diagram.
Specific implementation mode
To make the object, technical solutions and advantages of the present invention express to be more clearly understood, below in conjunction with the accompanying drawings and specifically
Case study on implementation is described in further details the present invention.
Fig. 1 show the color image encryption embedded mobile GIS flow chart the present invention is based on discrete domain, and this method includes following
Step：
Step 101：Secret Image characteristic coefficient is introduced in Logistic chaotic maps and Rabinovich hyperchaotic maps
Generate chaos sequence；
Step 102：Tri- channel pixel values of R, G, B of each pixel of image are reset using Logistic chaos sequences
It puts in order；
Step 103：Four groups of chaos sequences that Rabinovich hyperchaotic maps generate, using component masses scramble therein
Image pixel positions；
Step 104：After other three groups of Rabinovich Hyperchaotic Sequence subchannel scrambles and diffusion image DWT transformation
Low frequency coefficient；
Step 105：Encrypted image is embedded into public image DWT using least significant bit scrambling algorithm (LSB) to become
In high frequency coefficient after changing.
Fig. 2 show image encryption partial process view of the present invention, and specific method includes：
The lena.bmp coloured images that size is 512*512*3 are chosen, I is set asm×n(m=512, n=512).According to each logical
The pixel value x of road image slices vegetarian refreshmentsi, the average value E (x) in each channels image RGB is calculated by formula (1)：
Weighted average (weights are fixed) E' is calculated according to formula (2)：
E'=0.16 × ER+0.50×EG+0.34×EB (2)
Wherein ER、EG、EBThe average value of each channel pixel value of R, G, B is indicated respectively.
Weighted average is processed into impact factor Δ (as shown in formula (3)), the key as image decryption：
△=E' × 10-10 (3)
Since chaos system has strong sensibility and dependence to system initial value and parameter, need to will only influence because
Son is added on the initial value of Logistic chaotic maps and Rabinovich hyperchaotic maps, you can generate it is related to Secret Image and
Stable chaos sequence, including one group of Logistic chaos sequence and four groups of Rabinovich Hyperchaotic Sequences.
Logistic chaotic maps are a kind of common Chaos dynamic systems, have 3 kinds of forms, but full mapping range is small,
Cause numerical value change rate in iterative process small, and uniform distribution properties are not good enough.Therefore the present invention is using a kind of improved
Logistic chaotic maps, according to shown in formula (4)：Full mapping range is xn∈[-2β,2β]。
Wherein, xnIt is respectively state variable and control parameter, x with βnIndicate nth iteration value, xn+1For (n+1)th iteration
Value.Initialization system factor beta=10, at this time logistc mappings are in chaos state.Set its initial value x0It is 0.5, by △+x0Band
Enter system, pre- iteration Logistic chaotic maps N0=500 times, from N0+ 1 sequential value starts value, generates chaos sequence L1。
Rabinovich hyperchaotic maps are shown：
Wherein x, y, z, w indicate the state variable of Rabinovich hyperchaotic maps,Similarly
(wherein d indicates differential, and t is the time)；As systematic parameter a=4, b=-0.5, d=1, k=8.1, c=-2.2, calculate at this time
The maximum Lyapunov exponent (an important quantitative targets for weighing system dynamics) for obtaining the mapping is more than zero, there are two
Thus positive Lyapunov values, and Lyapunov dimensions are not integers judge) system is in chaos state.Using quadravalence dragon
Ge Kutafa solves equation (5), sets each state variable x, y, z, the initial value of w is respectively 0.8,0.5,12.1,
3.5.When phase space observes Rabinovich Hyperchaotic Sequences, has and select analog value to be set as initial value when preferable imaging.
Fourth order Runge-Kutta can be used to solve equation (5).System is brought into after △ is added on initial value, it is such as pre- to change
For N0=500 times, each sequence group is from N0+ 1 sequential value starts value, generates 4 groups of chaos sequences.
The line number and columns for reading secret coloured image I picture element matrixs are respectively m=512, n=512.It is m × n to take length
Logistic chaos sequences quantified, so that it is distributed in [0,1] range, be then converted into Lm×nMatrix, and with image I
Pixel correspond.Using each Logistic sequential values as criterion, the RGB sequences of its corresponding pixel points of scramble,
6 kinds of sortords, respectively RBG, GRB, GBR, BRG, BGR, RGB can be obtained.Scrambling process can be：
Step 1：Read in Logistic chaos sequence matrix Lsm×nWith coloured image Im×n, triple channel pixel pixel value point
It Wei not IrIgIb；
Step 2：If I'rI'gI'bFor three channel pixel pixel values of treated coloured image, then according to matrix
Lm×nIn each element value l replace the RGB sequences of the pixel corresponding to it：
if 0≤l≤1/6thenIg→I'b；Ib→I'g；(pixel RGB is sequentially converted into RBG at this time)
else if l≤1/3thenIr→I'g；Ig→I'r；(pixel RGB is sequentially converted into GRB at this time)
else if l≤1/2thenIr→I'b；Ig→I'r；Ib→I'g；(pixel RGB is sequentially converted into GBR at this time)
else if l≤2/3thenIr→I'g；Ig→I'b；Ib→I'r；(pixel RGB is sequentially converted into BRG at this time)
else if l≤5/6thenIr→I'b；Ib→I'r；(pixel RGB is sequentially converted into BGR at this time)
Else if l≤1then RGB sequences are constant；
end
Original image I obtains the image I after pixel RGB sequence scrambles after above-mentioned processing1。
Select 1 group of R in 4 groups of chaos sequences of Rabinovich hyperchaotic maps generation1To image pixel point position into
Line shuffle.Encryption efficiency is improved using the method for piecemeal scramble：Image is subjected to repeatedly different size of piecemeal processing, and block
Scramble, which intersects, between interior scramble and block carries out.Three kinds of level image piecemeal sizes are set：Minimum sub-block min=4, medium sub-block mid
=16 and maximum sub-block max=64, due to m, n can be divided exactly by min, mid and max, be handled without expansion.Block scramble step is such as
Under：
Step 1：Processing in smallest blocks block.By image I1It, will be in each smallest blocks after minimum sub-block min=4 piecemeals
Pixel do 180 ° of rotations and obtain I1'；
Step 2：Scramble between largest block block.Image I1' by maximum sub-block size max=64 piecemeals and number, often row and
Each column block number is respectively rmax=cmax=8；Take rmax×cmaxThe Rabinovich Hyperchaotic Sequences of=64 length, sequence obtain rope
Draw sequence In, then corresponding with the image block after piecemeal, is numbered from small to large according to new as the new number of piecemeal, and by image block
Sequence rearranges；
Step 3：Scramble in largest block block.Take first image block after resequencing in step 2 by min=4 piecemeals, row
Row block number is rm=cm=16, separately take rm×cmThe Rabinovich Hyperchaotic Sequences of=256 length are by its sequence scramble.It repeats
Operation, until obtaining image I by scramble in each largest block in step 21”；
Step 4：Scramble between medium sub-block block.By image I1" mid=16 piecemeals are pressed, ranks block number is rmid=cmid=32,
Separately take rmid×cmidThe Rabinovich Hyperchaotic Sequences of=1024 length are by its scramble；
That is image I1I is obtained after being handled in smallest blocks1', by I1' make to obtain I with scramble in block between maximum piecemeal block1",
Continue I1" make to obtain image I after scramble between medium piecemeal block2。
Image DWT transformation schematic diagrames are illustrated in figure 3, image is carried out to obtain figure after carrying out level-one Haar wavelet transformations
Low frequency component, horizontal component, vertical component and the diagonal components of picture, coefficient matrix are respectively that (wherein matrix is big by LL, HL, LH, HH
Small is m'/2 × n'/2).Wherein HL, LH, HH are high fdrequency component coefficient matrix, contain the detailed information of image, and low frequency system
Matrix number LL maintains the general picture and spatial character of original image, has concentrated most of energy of image.
Abundant experimental results, which show to encrypt low frequency coefficient matrix scrambling, can effectively avoid information leakage and improves safety.
The present invention by the domains the DWT low frequency component coefficient matrix of image after the scramble of preliminary pixel point position by making scramble and diffusion, to reach
To the purpose for spreading image pixel value.Diffusing step is as follows：
Step 1：By image I after the scramble of pixel position2RGB triple channels separation, and respectively carry out DWT transformation, obtain
Each channel factor matrix L L, and it is converted into the one-dimension array LL that length is 256 × 256.It is super using remaining 3 groups of Rabinovich
Chaos sequence R2、R3、R4Corresponding with each channel, length is identical, sorts by size to obtain its index sequence IniAfter (i=2,3,4), point
It is not corresponding with the one-dimension array LL that each channel low frequency coefficient matrix of image R, G, B is converted into, by IniAs each channel LLiNew sequence
Number, rearrangement obtains the coefficient LL' of position scramble.
Step 2：To R2、R3、R4Make following formula such as to handle：
Ri'=mod (floor (1000*abs (Ri),MaxLL), (i=2,3,4) (6)
Wherein Ri' three groups of sequential value after (i=1,2,3) expression processing, mod (a, b) indicates a to b division complementations,
Floor indicates that downward rounding, abs expressions take absolute value, MaxLLIndicate the integer part of maximum value in corresponding channel low frequency coefficient.
By pretreated three groups of sequence R1'、R2'、R3' respectively with corresponding channel coefficient LL' after scrambleiInteger portion
After point exclusive or (and keeping fractional part constant), it is converted into matrix, then obtains final scramble and the low frequency coefficient matrix after diffusion
LL”.Merging triple channel image obtains final encrypted image I after carrying out inverse transformation3。
It is image encryption part of the present invention above, and the inverse process that image decryption process is ciphering process.As long as correct
Key, you can decrypt Secret Image I.
Fig. 4 show comparison diagram before and after image RGB channel order rearrangement of the present invention, and Fig. 4 a are the channels artwork R, and Fig. 4 b are
The channels R after RGB sequence scrambles.
The present invention is encrypted using multiple keys, including original image weighted mean △, systematic parameter β and two are mixed
5 initial values of ignorant system.According to IEEE floating-point standards, 64 double-precision number computational accuracies are about 1015, then key space size
It is as shown in the table, it can be seen that resume image space of the present invention is sufficiently large, can resist exhaustive attack.
It is illustrated in figure 5 image encryption experimental result picture of the present invention.Fig. 5 (a) is that each pixel RGB sequences of image are set
Image after unrest, it can be seen that the color information of image is hidden；Fig. 5 (b) be it is after the further piecemeal scramble of image as a result,
It is apparent that in image lena people information be encrypted without that can recognize, at this time in each RGB channel of image each pixel whole
Random distribution in a image data；Fig. 5 (c) is final encrypted image；Fig. 5 (d) is test artwork；Fig. 5 (e) is that substitution is correct close
Decrypted image after key；Fig. 5 (f) is by correct key R1_ 0=0.8 is substituted for R1' _ 0=0.80000000000001 is substituted into
The wrong decrypted image of gained after decryption system.Initial value is merely through 1014Subtle change leads to decryption failure, illustrates the present invention
Algorithm is very sensitive to key, while it is high to resist exhaustive attack ability.
Fig. 6 is image graph 5 (d) and image graph 5 (c) histogram analysis comparison diagram after encryption before present invention encryption.It can be seen that
The histogram in tri- channels encrypted ciphertext image RGB and plaintext histogram data have the characteristics that it is high have it is low significantly different, and
And ciphertext histogram distribution is balanced.Therefore attacker will not therefrom obtain useful information to carry out statistical attack.
Fig. 7 is the channels the R correlation comparison diagram of image 5 (c) before and after image encryption of the present invention.After original image and encryption
Close figure carry out horizontal, the vertical correlation analysis between diagonal neighbor pixel, each direction randomly selects
2000 pairs of consecutive points carry out correlation calculations.Shown in correlation calculations formula such as formula (7-9)：
X and y indicates the pixel value of one group of neighbor pixel respectively in formula.ρ indicates related coefficient, and change can be characterized by being one
The amount of linear tight ness rating between amount, cov (x, y) indicate the covariance of x and y,Indicate the standard deviation of x,Indicate y
Standard deviation.
By following table data it is found that each channels original lena images RGB in the horizontal direction, the neighbour of vertical direction and diagonal
Related coefficient between pixel indicates that its neighbor pixel is highly relevant close to 1；And encrypted image is each logical
The related coefficient in road illustrates close to 0 by the way that after encryption system, the correlation of former plaintext image has substantially eliminated.Simultaneously by Fig. 6
Also it can intuitively find out the variation of the front and back correlation of encryption.
Image embedded part of the present invention is as follows：
Discrete wavelet transformer changes commanders the high frequency section of picture signal and low frequency part separates, and the two parts include
Different information.The approximate information of image is included in low frequency component, and is included in high fdrequency component about the information at edge.People
Eye is poor to the perception of edge information change, therefore (embedded secret figure can be modulated to the high fdrequency component of public image
Picture).And in order to reduce the influence to public image quality, the maximal bit digit that the present invention is embedded in is 4.
Open coloured image is chosen as carrier image, is set as IC, size is N × N, by image ICTriple channel is isolated
Each channel data ICr、ICg、ICb, prepare encrypted image I3Each channel data Ir、Ig、IbIt is embedded into image C corresponding channels
Data ICr、ICg、ICbIn.Illustrate image embedding grammar below for the channels R, G, channel B are similarly.First by ICrIt carries out twice
Haar wavelet transformations：First time wavelet transformation obtains low frequency coefficient Matrix C A (LL) (coefficient matrix CA as shown in Figure 8) and high frequency
Coefficient matrix CH (HL), CV (LH), CD (HH)；It is obtained respectively after doing second of wavelet transformation to three high frequency coefficient CH, CV, CD matrixes
The two level wavelet conversion coefficient matrix of the coefficient matrix of a high frequency coefficient matrix, CH is CHA, CHH, CHV, CHD, and the two level of CV is small
Wave conversion coefficient matrix is CVA, CVH, CVV, CVD, and the two level wavelet conversion coefficient matrix of CD is CDA, CDH, CDV, CDD, one
Totally 12 two level coefficient matrixes, as shown in Figure 8.Secret Image data are embedded into the high fdrequency component of second level wavelet conversion coefficient
In, can at most have 9 two level high frequency coefficient matrixes that can use, respectively CDD, CDH, CDV, CHD, CVD, CHH, CHV, CVH,
CVV.Embedded step is as follows：
Step 1：By RIIt is converted to binary message code stream (length M)；
Step 2：By CDD coefficient matrixes ((1) CDD in such as Fig. 8), size is N' × N', N'=N/4, be converted to it is one-dimensional to
It measures (V), then by RIBinary message code stream be embedded in obtained vector, telescopiny is as follows：
If a. M<2 × N' × N' then replaces 2 least significant bits of element in each V with 2 binary message code streams
(LSB), V' is obtained；
If b. M<3 × N' × N' then replaces 3 LSB of element in each V with 3 binary message code streams, obtains V'；
C. 4 LSB that element in each V is otherwise replaced with 4 binary message code streams, obtain V'；
D. the obtained vector (V') after embedding information is converted back into two-dimensional matrix CDD', is substituted into original old coefficient square
The position of battle array CDD；
Step 3：If information code current is not embedded into when 4 LSB of CDD are embedding full and finishes, successively in remaining 8 high frequencies
Coefficient matrix：Step 2 is repeated in CDH, CDV, CHD, CVD, CHH, CHV, CVH, CVV continues embedded remaining information code stream, until
(coefficient matrix CDH (2), CDV (3), CHD (4), CVD (5), CHH (6), CHV (7), CVH in such as Fig. 8 are completed in information code current insertion
(8), (9) CVV, label represent embedded sequence).So far, each coefficient matrix after being modulated.
Step 4：DWT transformation is carried out to coefficient matrix CDA.By the coefficient matrix number used in above step and last embedding
Enter the number of bits used in the coefficient matrix of information, is embedded into third level coefficient CDAD (coefficient matrix CDAD in such as Fig. 8
It is shown), then inverse transformation obtains CDA'.
After the completion of telescopiny, after coefficients at different levels are taken turns doing IDWT, merge RGB tri- channels, then obtain being embedded in plus
The public image C' of Mi Mitu.
The lifted embodiment of the present invention or embodiment have carried out further the object, technical solutions and advantages of the present invention
Detailed description, it should be understood that embodiment provided above or embodiment be only the preferred embodiment of the present invention and
, be not intended to limit the invention, all within the spirits and principles of the present invention it is made for the present invention it is any modification, equally replace
It changes, improve, should all be included in the protection scope of the present invention.
Claims (9)
1. a kind of color image encryption embedding grammar based on discrete domain, which is characterized in that include the following steps：Step 101：It will
Secret Image characteristic coefficient is introduced into Logistic chaotic maps and Rabinovich hyperchaotic maps, is generated and Secret Image phase
The chaos sequence of pass；Step 102：RGB using each pixel of sequence reorganization image of Logistic chaotic maps generation is suitable
Sequence eliminates the color information of coloured image；Step 103：The four groups of chaos sequences generated using Rabinovich hyperchaotic maps
In one group of sequence piecemeal scramble image pixel positions；Step 104：Using in remaining three groups of Rabinovich Hyperchaotic Sequences
Sequence scramble Secret Image pixel position and the domains diffusion image wavelet transform DWT low frequency coefficient, obtain encrypted image；Step
Rapid 105：Encrypted image is embedded into the high frequency coefficient after public image DWT transformation, concealed encrypted image information.
2. according to the method described in claim 1, it is characterized in that, the introducing characteristics of image coefficient to one-dimensional chaos system into
One step includes：The average value for calculating the secret each channels coloured image RGB, impact factor is obtained after weighted average is reduced
Impact factor is added in Logistic chaotic maps and Rabinovich hyperchaotic maps by the key of △, △ as image decryption
Initial value on, generate and the relevant chaos sequence of Secret Image, including one group of Logistic chaos sequence and four groups
Rabinovich Hyperchaotic Sequences.
3. according to the method described in claim 1, it is characterized in that, the RGB sequences for resetting image slices vegetarian refreshments include reading secret
Coloured image I, the line number and columns of image I picture element matrixs are respectively m, n, take length be m × n Logistic chaos sequences into
Row quantization, makes it be distributed in [0,1] range, is then converted into and the one-to-one matrix L of the pixel of image Im×n, with every
A Logistic sequential values reset the RGB sequences of its corresponding pixel points, obtain resetting image I as criterion1。
4. according to the method described in claim 1, it is characterized in that, using the component masses in Rabinovich Hyperchaotic Sequences
Scramble image pixel positions include：Select the one of which in four groups of chaos sequences of Rabinovich hyperchaotic maps generation mixed
Image I after ignorant sequence pair rearrangement1Into line shuffle, scramble intersects and carries out between scramble and block in block, resets image I for pixel position1
Image I after the scramble of pixel position is obtained after piecemeal disorder processing2。
5. according to one of them described method of claim 1-4, which is characterized in that encrypted image is embedded into high frequency
It is specifically included in coefficient：The high frequency section and low frequency part of wavelet transform separating image signals, it is N × N's to choose size
Coloured image C is as carrier image IC, by carrier image ICThe isolated each channel data I of triple channelCr、ICg、ICb, will count respectively
According to ICr、ICg、ICbThe high frequency coefficient matrix that wavelet transformation obtains twice is carried out, second of small echo is done again to the high frequency coefficient matrix
Become the coefficient matrix for getting each high frequency coefficient matrix in return, by encrypted image I3Each channel data Ir、Ig、IbIt is embedded into the second level
In the high fdrequency component of wavelet conversion coefficient.
6. according to the method described in one of claim 1-4, which is characterized in that the scramble Secret Image pixel position
For by each channel pixel random scrambling in triple channel, the diffusion image low frequency coefficient is the low frequency coefficient of image discrete domain
The diffusion of value, the concealed encrypted image information are that encrypted image is embedded in the high frequency coefficient of public image discrete domain to work as
In.
7. according to the method described in claim 2, it is characterized in that, the full mapping range of Logistic chaotic maps is xn∈[-2
β, 2 β],Wherein, β parameters in order to control, xnState variable nth iteration value is indicated, when β ∈ (0, ∞)
When, logistc mappings are in chaos state；Rabinovich hyperchaotic maps are：
Wherein x, y, z, w indicate the state variable of Rabinovich hyperchaotic maps,A, b, d, k, c are dynamic for measurement system
The systematic parameter of mechanical characteristic.
8. according to the method described in claim 4, it is characterized in that, utilizing remaining three groups of chaos sequence in four dimensional chaos sequence
Scramble further comprises with diffusion low frequency coefficient：Using Haar wavelet basis functions, respectively to image I2R, G, channel B carry out one
The high fdrequency component coefficient matrix and low frequency coefficient matrix in each channel of image are obtained after grade wavelet transformation, utilizes three groups of chaos sequences point
The other low frequency coefficient matrix to each channel into line shuffle, then by the integer part of each coefficient in the low frequency coefficient matrix after scramble with
Rabinovich Hyperchaotic Sequence step-by-step exclusive or obtains the encrypted image I after pixel value diffusion3。
9. according to the method described in claim 4, it is characterized in that, the piecemeal scramble specifically includes：It is big that three kinds of ranks are set
Small image block：Minimum sub-block min, medium sub-block mid, maximum sub-block max, wherein max can be divided exactly by min；By image I1
Expansion handles to obtain image I'm'×n', wherein m' >=m, n' >=n so that m' and n' can be divided exactly by min, mid and max.
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