CN113115053B - Image encryption method based on integer wavelet transform and compressed sensing - Google Patents
Image encryption method based on integer wavelet transform and compressed sensing Download PDFInfo
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Abstract
The invention provides an image encryption method based on integer wavelet transform and compressed sensing, which solves the problem of insufficient encryption safety in the mode of directly embedding a carrier after compressed sensing in the current airspace image encryption method based on compressed sensing; then, performing sparse processing on the preprocessed plaintext image, and sequentially performing scrambling operation; generating a measuring matrix, carrying out compressed sensing on the plaintext image after the scrambling operation by using the measuring matrix, executing diffusion operation before embedding the carrier image, further improving the security of image encryption, finally obtaining a frequency coefficient by using integer wavelet transformation, carrying out embedding operation on the carrier image, and then executing inverse integer wavelet transformation, thereby reducing data loss caused by frequency domain transformation and improving the encryption security of image information.
Description
Technical Field
The invention relates to the technical field of image encryption, in particular to an image encryption method based on integer wavelet transform and compressive sensing.
Background
With the rapid development of internet technology and social media, more and more multimedia information is generated and spread on the internet. In the digital information, digital images are an information format that can transmit information in a visual manner, but some privacy images exist in the digital images, and the privacy images have certain risks in being transmitted on a network. In order to prevent such digital images containing a large amount of private information from being acquired or utilized by unauthorized persons, image encryption has attracted considerable attention as an effective means.
Digital image encryption can be divided into two types of modes of frequency domain encryption and space domain encryption according to different encryption domains. The spatial domain encryption is that a digital image is used as a two-dimensional matrix, and the two-dimensional matrix is subjected to reversible transformation from the perspective of space. The common spatial domain image encryption scheme includes two stages of scrambling and diffusion, the frequency domain is relative to the spatial domain of the image, the image is processed from the frequency domain space, and the conversion between the spatial domain and the frequency domain of the image can be realized by using the transformation methods such as discrete cosine transform, fast fourier transform, wavelet transform and the like. The frequency domain encryption scheme is characterized by high encryption speed, but generally belongs to lossy encryption, namely, a decrypted image has a small difference from a plaintext image.
The compressive sensing theory is a novel signal sampling theory, and can effectively capture and recover signals by setting an underdetermined linear system. The compressed sensing theory explores how to achieve the same signal reconstruction accuracy at a lower sampling rate. Since digital images have high redundancy properties, some unnecessary processes are generated when processing the images. Compressed sensing can just reduce the redundancy of data. Before data transmission, if the ciphertext image can be further compressed, the efficiency can be improved, and the method is more suitable for a transmission channel with limited broadband. The encrypted image has texture-like or noise-like features which attract the attention of an attacker, so that the attack rate of the encrypted image information in transmission is improved. The image hiding technology can reduce the potential attack threat, and in combination with the information hiding technology, the original image is embedded into the processed carrier image after being encrypted, so that the visually meaningful image encryption technology is realized, and the possibility of the image being attacked is reduced to some extent.
In 2019, 19.2.2019, a Chinese patent application with publication number CN109360141A discloses an image encryption method based on compressed sensing and three-dimensional cat mapping, which includes the steps of firstly calculating an initial state value and system parameters of a three-dimensional cat mapping chaotic system according to a pixel average value of a plaintext image, then scrambling a sparse coefficient matrix of the plaintext image, constructing a measurement matrix, and performing compressed measurement on the scrambled sparse coefficient matrix to obtain a ciphertext image, and embedding the ciphertext image into a carrier image by using an embedding algorithm based on the carrier image to obtain a visual security image, so that the ciphertext image is visually secure, and the defect that a decrypted image obtained by a frequency domain encryption method at last is different from the plaintext image is overcome.
Disclosure of Invention
In order to solve the problem of insufficient encryption security in the current spatial domain image encryption method based on compressed sensing in a mode of directly embedding a carrier after compressed sensing, the invention provides an image encryption method based on integer wavelet transform and compressed sensing.
In order to achieve the technical effects, the technical scheme of the invention is as follows:
an image encryption method based on integer wavelet transform and compressed sensing comprises the following steps:
s1, selecting a chaotic system, setting an initial value of the chaotic system, determining a plaintext image P with the size of M multiplied by N, pixels and S, and preprocessing the plaintext image P;
s2, substituting M, N, S and the initial value into the chaotic system for iteration to generate a random sequence, and performing pretreatment and quantization to obtain a quantized random sequence;
s3, performing sparse processing on the preprocessed plaintext image P, and scrambling the sparse processed plaintext image P by using a quantized random sequence;
s4, generating a measurement matrix, performing compressed sensing on the scrambled plaintext image P by using the measurement matrix, and then quantizing and combining to obtain D;
s5, performing diffusion operation on the D to obtain a ciphertext image E;
s6, introducing a carrier image Q, carrying out integer wavelet transformation on the carrier image to obtain a frequency coefficient, splitting a ciphertext image E, embedding the ciphertext image E into the frequency coefficient, and then carrying out inverse integer wavelet transformation on the frequency coefficient to obtain a final visual security image F.
Preferably, the process of preprocessing the plaintext image P in step S1 is: dividing a plaintext picture P into four sub-pictures P i I =1,2,3,4,i represents the number of the subgraph; wherein, odd rows and odd columns of the plaintext image P are extracted to form a first sub-image P 1 Extracting odd-numbered rows and even-numbered columns of the plaintext image P to form a second sub-image P 2 Extracting the even rows and odd columns of the plaintext image P to form a third sub-image P 3 Extracting even rows and even columns of the plaintext image P to form a fourth sub-image P 4 。
Preferably, the initial value of the chaotic system is set to x 0 ,y 0 ,z 0 In step S2, the number of iterations performed by substituting M, N, S and the initial value into the chaotic system is M × N + S, and M × N numbers are taken from 1+S to generate three random sequences x, y, and z with a length of M × N, where the formula for preprocessing the random sequences x, y, and z is:
wherein, x ', y', z 'represents the random sequence after the pretreatment, and the formula for continuously carrying out the quantization processing on x', y ', z' is as follows:
wherein X, Y and Z represent quantized random sequences obtained after the quantization processing of X ', Y ' and Z '. The random sequences x, y and z are preprocessed to enable the random sequences x, y and z to have stronger randomness, the subsequent quantization processing is mapping, the random sequences generated by the chaotic system are associated with plaintext image information, and known plaintext attacks and plaintext attack selection attacks are resisted strongly.
Preferably, the pre-processed plaintext image P has been divided into four sub-images P i I =1,2,3,4,i represents the number of the subgraphs, and in step S3, the clearness is shownIth sub-picture P of text picture P i The formula for performing the sparse processing is as follows:
A i ＝Psi×P i ×Psi'i＝1,2,3,4
where Psi denotes the sparse basis, obtained by DWT function, A i The ith sub-map after the thinning-out process is shown.
Preferably, the process of scrambling the sparse plaintext image P by using the quantized random sequence is as follows:
sequencing Y of the quantized random sequence to obtain an index sequence SY;
scrambling operation is carried out on the plaintext image P after sparse processing, and the plaintext image P after scrambling operation is set to be represented as B i I =1,2,3,4, satisfying the formula:
B i (j)＝A i (SY(j))；
wherein j =1,2,3 …, M/2 × N/2.
Preferably, the process of generating the measurement matrix in step S4 is:
extracting the front M/2 number from the X of the quantized random sequence to form a sequence X ', and sequencing the sequence X' to obtain an index sequence SX;
the compression ratio of the chaotic system is set as CR, a Hadamard matrix H is utilized to generate a measurement matrix, and the formula is as follows:
Phi＝H(SX(1:CR*M/2),:)
phi represents a measurement matrix, and the random sequence of the chaotic system is used for controlling and generating the measurement matrix, so that the transmission of the measurement matrix is reduced.
Preferably, the plaintext image P after the scrambling operation is denoted B i I =1,2,3,4, and the expression for compressed sensing of the plaintext image P after scrambling operation is:
C i ＝Phi×B i
wherein, C i Represents the compressed perceived image, i =1,2,3,4, for C i Carrying out quantization and combination to obtain D i I =1,2,3,4, integrated as D, wherein D i The solving formula of (2) is as follows:
D i ＝255+255×(C i -max(C i (:)))/(max(C i (:))-min(C i (ii))) in which the total number of pixels is not changed even though the image is scrambled, and C is quantized and combined i Is mapped to [0-255 ]]In preparation for subsequent embedding operations.
Preferably, the step S5 of performing the diffusion operation on D to obtain the ciphertext image E includes the specific processes of:
setting the size of D as md × nd, recombining the random sequence Z into a matrix W with the size of md × nd, and when performing diffusion operation on D, firstly performing addition-modulo diffusion on D in the row direction, and then performing addition-modulo diffusion on D in the column direction to obtain a ciphertext image E, wherein the process meets the formula:
wherein p =1,2,3, …, md; k =1,2,3, …, nd, the diffusion operation further improves the security of image encryption.
Preferably, the size of the carrier image Q in step S6 is 2 mx 2N, the integer wavelet transform performed on the carrier image is a two-level integer wavelet transform, and the size after the two-level integer wavelet transform is: m/2 XN/2, and the obtained frequency coefficients are LL, HL, LH and HH;
determining the size of a ciphertext image E according to the compression ratio CR of the chaotic system, splitting the ciphertext image E according to the size of the ciphertext image E, embedding the split ciphertext image E into corresponding frequency coefficients of LL, HL, LH and HH, and performing inverse integer wavelet transform on the frequency coefficients to obtain a final visual security image F.
Preferably, the inverse integer wavelet transform performed on the frequency coefficients is a quadratic inverse integer wavelet transform.
In the method, the ciphertext image E is embedded into the carrier image Q by combining an information hiding technology, so that the safety hiding effect of image information is improved, reversibility is realized by using integer wavelet transformation and inverse integer wavelet transformation, and data loss caused by frequency domain transformation can be reduced.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
the invention provides an image encryption method based on integer wavelet transform and compressive sensing, which is characterized in that a plaintext image is preprocessed, then iteration is carried out in a chaotic system to generate a random sequence, and the random sequence is preprocessed and quantized to obtain a quantized random sequence, so that the random sequence has stronger randomness; then, the preprocessed plaintext image is subjected to sparse processing, a quantized random sequence is used for scrambling the plaintext image subjected to sparse processing to generate a measurement matrix, the measurement matrix is used for carrying out compressed sensing on the plaintext image subjected to scrambling operation, the random sequence of a chaotic system is used for controlling and generating the measurement matrix, transmission of the measurement matrix is reduced, diffusion operation is carried out before embedding a carrier image, the security of image encryption is further improved, the problem that encryption security is insufficient in the mode that the carrier is directly embedded after compressed sensing in the current spatial domain image encryption method based on compressed sensing is solved, finally, integer wavelet transformation is carried out on the carrier image to obtain a frequency coefficient, a ciphertext image is split and embedded into the frequency coefficient, then inverse integer wavelet transformation is carried out on the frequency coefficient, reversibility can be achieved through the integer wavelet transformation, data loss caused by frequency domain transformation is reduced, and the encryption security of image information is improved.
Drawings
Fig. 1 is a flowchart of an image encryption method based on integer wavelet transform and compressive sensing proposed in an embodiment of the present invention;
fig. 2 is a schematic diagram of a specific plaintext image House according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a ciphertext image obtained by encrypting the plaintext image shown in FIG. 2 by using the image encryption method according to the disclosure;
FIG. 4 shows a schematic diagram of a specific carrier image Pentagon proposed in an embodiment of the present invention;
FIG. 5 is a schematic diagram of a final visual security image with a ciphertext image embedded in a carrier image in an embodiment of the invention;
FIG. 6 is a diagram of a plaintext image after decryption of an image encrypted by the encryption method according to the present invention;
fig. 7 shows a histogram of the carrier image Pentagon corresponding to fig. 4;
FIG. 8 shows a histogram of the final visual security image;
FIG. 9 shows a histogram of the corresponding plaintext image House of FIG. 2;
FIG. 10 shows a histogram of a ciphertext image;
fig. 11 shows a histogram of the decrypted plaintext image.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
for better illustration of the present embodiment, certain parts of the drawings may be omitted, enlarged or reduced, and do not represent actual dimensions;
it will be understood by those skilled in the art that certain well-known descriptions of the figures may be omitted.
The positional relationships depicted in the drawings are for illustrative purposes and are not to be construed as limiting the present patent;
the technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Examples
The image encryption method based on integer wavelet transform and compressed sensing as shown in fig. 1 comprises the following steps:
s1, selecting a chaotic system, setting an initial value of the chaotic system, determining a plaintext image P with the size of M multiplied by N, pixels and S, and preprocessing the plaintext image P; in this embodiment, a specific plaintext image is selected as shown in fig. 2.
The specific process of preprocessing the plaintext image P is as follows: dividing the plaintext image P into four subgraphs Pi, wherein i =1,2,3,4, i represents the sequence number of the subgraphs; wherein, odd rows and odd columns of the plaintext image P are extracted to form a first sub-image P 1 Extracting odd-numbered rows and even-numbered columns of the plaintext image P to form a second sub-image P 2 Extracting a plaintext imageThe even rows and odd columns of P form a third sub-diagram P 3 Extracting even rows and even columns of the plaintext image P to form a fourth sub-image P 4 (ii) a In addition, the initial value of the chaotic system is set to x 0 ＝0.067,y 0 ＝0.247,z 0 ＝0.863；
S2, substituting M, N, S and the initial value into the chaotic system for iteration to generate a random sequence, and performing pretreatment and quantization to obtain a quantized random sequence;
m, N, S and the initial value are substituted into the chaotic system for iteration times of M × N + S times, M × N numbers are taken from 1+S, three random sequences x, y and z with the length of M × N are generated, and a formula for preprocessing the random sequences x, y and z is as follows:
wherein, x ', y', z 'represents the random sequence after the pretreatment, and the formula for continuously carrying out the quantization processing on x', y ', z' is as follows:
wherein X, Y and Z represent quantized random sequences obtained after the quantization processing of X ', Y ' and Z '. The random sequences x, y and z are preprocessed to enable the random sequences x, y and z to have stronger randomness, the subsequent quantization processing is mapping, the random sequences generated by the chaotic system are associated with plaintext image information, and known plaintext attacks and plaintext attack selection attacks are resisted strongly.
S3, performing sparse processing on the preprocessed plaintext image P, and scrambling the sparse processed plaintext image P by using a quantized random sequence, so that encryption and hiding of the first layer of image information are realized;
in practical implementation, four sub-graphs P obtained after partitioning are respectively subjected to i (i =1,2,3,4) to obtain A i (i =1,2,3,4), for the ith sub-picture P of the plaintext picture P i The formula for performing the sparse processing is as follows:
A i ＝Psi×P i ×Psi'i＝1,2,3,4
where Psi denotes the sparse basis, obtained by DWT function, A i The ith sub-map after the thinning-out process is shown.
Sequencing Y of the quantized random sequence to obtain an index sequence SY;
scrambling operation is carried out on the plaintext image P after sparse processing, and the plaintext image P after scrambling operation is set to be represented as B i I =1,2,3,4, satisfying the formula:
B i (j)＝A i (SY(j))；
wherein j =1,2,3 …, M/2 × N/2.
S4, generating a measurement matrix, performing compressed sensing on the scrambled plaintext image P by using the measurement matrix, and then quantizing and combining to obtain D, wherein the step realizes encryption and hiding of second-layer image information;
extracting the front M/2 number from the X of the quantized random sequence to form a sequence X ', and sequencing the sequence X' to obtain an index sequence SX;
let the compression ratio of the chaotic system be CR, in this embodiment, CR is 0.5, and a measurement matrix is generated by using a hadamard matrix H, where the formula is:
Phi＝H(SX(1:CR*M/2),:)
phi represents a measurement matrix, and the random sequence of the chaotic system is utilized to control and generate the measurement matrix, so that the transmission of the measurement matrix is reduced; the plaintext image P after the scrambling operation is denoted as B i I =1,2,3,4, and the expression for compressed sensing of the plaintext image P after the scramble operation is:
C i ＝Phi×B i
wherein, C i Represents the compressed perceived image, i =1,2,3,4, for C i Carrying out quantization combination to obtain D i I =1,2,3,4, integrated as D, wherein D i The solving formula of (2) is as follows:
D i ＝255+255×(C i -max(C i (:)))/(max(C i (:))-min(C i (:))) where the total number of pixels is unchanged although the image is subjected to the scrambling operation,performing quantization and combination to obtain C i Is mapped to [0-255 ]]In preparation for subsequent embedding operations.
S5, performing diffusion operation on the D to obtain a ciphertext image E, wherein the step realizes encryption and hiding of the first layer of image information, and a schematic diagram of the ciphertext image obtained after encryption is shown in FIG. 3.
Only the position of the pixels in the single block is changed due to the preceding scrambling operation. In order to further improve the security, the diffusion operation is performed on the integrated image D, and the diffusion operation in the row direction is performed first, and then the diffusion operation in the column direction is performed. Setting the size of D as md x nd, recombining the random sequence Z into a matrix W with the size of md x nd, when performing diffusion operation on D, firstly performing addition-modulo diffusion on D in the row direction, and then performing addition-modulo diffusion on D in the column direction to obtain a ciphertext image E, wherein the process meets the formula:
wherein p =1,2,3, …, md; k =1,2,3, …, nd, the diffusion operation further improves the security of image encryption.
S6, introducing a carrier image Q, carrying out integer wavelet transform on the carrier image to obtain a frequency coefficient, splitting a ciphertext image E, embedding the ciphertext image E into the frequency coefficient, and then carrying out inverse integer wavelet transform on the frequency coefficient to obtain a final visual security image F.
In this embodiment, as shown in fig. 4, a carrier image Pentagon is adopted, the size of the carrier image is 2 mx 2N, a secondary integer wavelet transform is performed on the carrier image, the integer wavelet transform performed on the carrier image is a secondary integer wavelet transform, and the size after the secondary integer wavelet transform is: m/2 XN/2, and the obtained frequency coefficients are LL, HL, LH and HH;
determining the size of a ciphertext image E according to the compression ratio CR of the chaotic system, splitting the ciphertext image E according to the size of the ciphertext image E, embedding the split ciphertext image E into corresponding frequency coefficients in LL, HL, LH and HH, wherein the size of the ciphertext image E obtained after encryption of an MxN plaintext image P is M/2 xN because the compression ratio CR =0.5, and the size of a carrier image Q after secondary integer wavelet transformation is M/2 xN/2. So the ciphertext image E is split into two matrices E _ left, E _ right of size M/2 × N/2, E _ left is embedded into LH, E _ right is embedded into HH, let the embedding coefficient be α =0.1, and the embedding formula be:
performing inverse integer wavelet transform on LL, HL, LH ', HH' to obtain a final visual security image F, which also implements encryption and concealment of image information of the fourth layer, fig. 5 shows a schematic diagram of a final visual security image in which a ciphertext image is embedded into a carrier image, and embedding a ciphertext image E into a carrier image Q by combining an information concealment technique, thereby enhancing the security and concealment effect of image information, and implementing reversibility by using integer wavelet transform and inverse integer wavelet transform, and reducing data loss caused by frequency domain transform.
In order to further verify the effectiveness, the security and the decryption reconstruction effect of the method provided by the invention, the invention further continues to use the visual security image shown in fig. 5, the carrier image shown in fig. 4 and the initial value x required by the chaotic system according to the symmetry principle 0 ＝0.067,y 0 ＝0.247,z 0 And (4) taking the =0.863 as input decryption, substituting the initial value into the chaotic system for iterative calculation to obtain a key stream, and quantizing the key stream according to a mathematical model. And performing inverse operation, namely performing secondary integer wavelet transform on the visual security image F, extracting a ciphertext image by combining the carrier image Q, then performing inverse diffusion, inverse quantization, reconstruction, compressed sensing recovery, and decrypting the plaintext image to the security level as shown in fig. 6, wherein fig. 7 shows a histogram of the carrier image Pentagon in fig. 4, and fig. 8 is a histogram of the visual security image. It can be seen that the histogram of the carrier image is almost the same as the histogram of the visual image, which shows that the hidden effect of the ciphertext image of the invention is good and the visual expressive force is strong, fig. 9 is the histogram of the plaintext image House, fig. 10 is the histogram of the ciphertext image, and it can be seen that the plaintext imageThe histogram of the ciphertext image is flat, so the method thoroughly changes the statistical characteristics of the image data, has good encryption effect, and aiming at the decryption process, fig. 11 shows the histogram of the decrypted image, which is similar to the histogram of the plaintext image shown in fig. 9, and shows that the decryption reconstruction effect of the invention is good.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (10)
1. An image encryption method based on integer wavelet transform and compressed sensing is characterized by comprising the following steps:
s1, selecting a chaotic system, setting an initial value of the chaotic system, determining a plaintext image P with the size of M multiplied by N, pixels and S, and preprocessing the plaintext image P;
s2, substituting M, N, S and the initial value into the chaotic system for iteration to generate a random sequence, and performing pretreatment and quantization to obtain a quantized random sequence;
s3, performing sparse processing on the preprocessed plaintext image P, and scrambling the sparse processed plaintext image P by using a quantized random sequence;
s4, generating a measurement matrix, performing compressed sensing on the disordered plaintext image P by using the measurement matrix, and then performing quantization and combination to obtain D;
s5, performing diffusion operation on the D to obtain a ciphertext image E;
s6, introducing a carrier image Q, carrying out integer wavelet transformation on the carrier image to obtain a frequency coefficient, splitting a ciphertext image E, embedding the ciphertext image E into the frequency coefficient, and then carrying out inverse integer wavelet transformation on the frequency coefficient to obtain a final visual security image F.
2. The image encryption method based on integer wavelet transform and compressed sensing according to claim 1, wherein the process of preprocessing the plaintext image P in step S1 is as follows: dividing a plaintext picture P into four sub-pictures P i I =1,2,3,4,i denotes the number of the subgraph; wherein, odd rows and odd columns of the plaintext image P are extracted to form a first sub-image P 1 Extracting odd-numbered rows and even-numbered columns of the plaintext image P to form a second sub-image P 2 Extracting the even rows and odd columns of the plaintext image P to form a third sub-image P 3 Extracting even rows and even columns of the plaintext image P to form a fourth sub-image P 4 。
3. The image encryption method based on integer wavelet transform and compressed sensing of claim 2, wherein the initial value of the chaotic system is set as x 0 ,y 0 ,z 0 In step S2, the number of iterations performed by substituting M, N, S and the initial value into the chaotic system is M × N + S times, and M × N numbers are taken from 1+S to generate three random sequences x, y, and z with a length of M × N, where the formula for preprocessing the random sequences x, y, and z is:
wherein, x ', y', z 'represents the random sequence after the pretreatment, and the formula for continuously carrying out the quantization processing on x', y ', z' is as follows:
wherein X, Y and Z represent quantized random sequences obtained after the quantization processing of X ', Y ' and Z '.
4. The method of claim 3The image encryption method based on integer wavelet transform and compressed sensing is characterized in that a preprocessed plaintext image P is divided into four sub-images P i I =1,2,3,4,i indicates the number of sub-pictures, and in step S3, for the i-th sub-picture P of the plaintext picture P i The formula for performing the sparse processing is as follows:
A i ＝Psi×P i ×Psi' i＝1,2,3,4
where Psi denotes the sparse basis, obtained by DWT function, A i The ith sub-map after the thinning-out process is shown.
5. The image encryption method based on integer wavelet transform and compressed sensing according to claim 4, characterized in that the process of scrambling the sparsely processed plaintext image P by using the quantized random sequence is as follows:
sequencing Y of the quantized random sequence to obtain an index sequence SY;
scrambling operation is carried out on the plaintext image P after sparse processing, and the plaintext image P after scrambling operation is set to be represented as B i I =1,2,3,4, satisfying the formula:
B i (j)＝A i (SY(j))；
wherein j =1,2,3 …, M/2 × N/2.
6. The image encryption method based on integer wavelet transform and compressed sensing according to claim 5, wherein the process of generating the measurement matrix in step S4 is:
extracting the front M/2 number from the X of the quantized random sequence to form a sequence X ', and sequencing the sequence X' to obtain an index sequence SX;
the compression ratio of the chaotic system is set as CR, a Hadamard matrix H is utilized to generate a measurement matrix, and the formula is as follows:
Phi＝H(SX(1:CR*M/2),:)
where Phi denotes a measurement matrix.
7. The image encryption method based on integer wavelet transform and compressive sensing as claimed in claim 6, whereinThen, the plaintext image P after scrambling operation is represented as B i I =1,2,3,4, and the expression for compressed sensing of the plaintext image P after scrambling operation is:
C i ＝Phi×B i
wherein, C i Represents the compressed perceived image, i =1,2,3,4, for C i Carrying out quantization combination to obtain D i I =1,2,3,4, integrated as D, where D i The solving formula of (2) is as follows:
D i ＝255+255×(C i -max(C i (:)))/(max(C i (:))-min(C i (:)))。
8. the image encryption method based on integer wavelet transform and compressed sensing of claim 7, wherein the step S5 of performing diffusion operation on D to obtain the ciphertext image E comprises the following specific processes:
and (2) setting the size of D as md × nd, recombining the quantized random sequence Z into a matrix W with the size of md × nd, and performing modulo diffusion on D in the row direction and then in the column direction to obtain a ciphertext image E when performing diffusion operation on D, wherein the process meets the formula:
wherein p =1,2,3, …, md; k =1,2,3, …, nd.
9. The image encryption method based on integer wavelet transform and compressed sensing of claim 8, wherein the size of the carrier image Q in step S6 is 2 mx 2N, the integer wavelet transform performed on the carrier image is a secondary integer wavelet transform, and the size of the carrier image Q after the secondary integer wavelet transform is: m/2 XN/2, and the obtained frequency coefficients are LL, HL, LH and HH;
determining the size of a ciphertext image E according to the compression ratio CR of the chaotic system, splitting the ciphertext image E according to the size of the ciphertext image E, embedding the split ciphertext image E into corresponding frequency coefficients of LL, HL, LH and HH, and performing inverse integer wavelet transform on the frequency coefficients to obtain a final visual security image F.
10. The integer wavelet transform and compressed sensing-based image encryption method of claim 9, wherein the inverse integer wavelet transform performed on the frequency coefficients is a quadratic inverse integer wavelet transform.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004126484A (en) * | 2002-10-01 | 2004-04-22 | Chaos Sangyo Gijutsu Kenkyusho:Kk | Method for compressing and ciphering image data |
| CN105513002A (en) * | 2015-11-30 | 2016-04-20 | 广东海洋大学 | Novel image encryption method based on correlation between chaos and plaintext |
| CN105704500A (en) * | 2016-03-17 | 2016-06-22 | 哈尔滨工业大学（威海） | Novel chaos-based image lossless compression encryption joint algorithm |
| CN106778304A (en) * | 2016-12-09 | 2017-05-31 | 交通运输部水运科学研究所 | A kind of quick New chaotic image encryption method with related scramble mechanism in plain text |
| CN111932430A (en) * | 2020-01-15 | 2020-11-13 | 南京信息工程大学 | Image encryption method based on FPGA |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| US7349542B2 (en) * | 2002-07-25 | 2008-03-25 | Georgia Tech Research Corporation | Systems, methods and computer program products for encryption and decryption using wavelet transforms |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004126484A (en) * | 2002-10-01 | 2004-04-22 | Chaos Sangyo Gijutsu Kenkyusho:Kk | Method for compressing and ciphering image data |
| CN105513002A (en) * | 2015-11-30 | 2016-04-20 | 广东海洋大学 | Novel image encryption method based on correlation between chaos and plaintext |
| CN105704500A (en) * | 2016-03-17 | 2016-06-22 | 哈尔滨工业大学（威海） | Novel chaos-based image lossless compression encryption joint algorithm |
| CN106778304A (en) * | 2016-12-09 | 2017-05-31 | 交通运输部水运科学研究所 | A kind of quick New chaotic image encryption method with related scramble mechanism in plain text |
| CN111932430A (en) * | 2020-01-15 | 2020-11-13 | 南京信息工程大学 | Image encryption method based on FPGA |
Non-Patent Citations (1)
| Title |
|---|
| Spatial image encryption algorithm based on chaotic map and pixel frequency;Guodong YE 等;《SCIENCE CHINA Information Sciences》;20171020;第1-3页 * |
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