Images are the most important carrier of human information. Moreover, how to safely transmit digital imagesthrough public channels has become an urgent problem. In this paper, we propose a novel image encryptionalgori...Images are the most important carrier of human information. Moreover, how to safely transmit digital imagesthrough public channels has become an urgent problem. In this paper, we propose a novel image encryptionalgorithm, called chaotic compressive sensing (CS) encryption (CCSE), which can not only improve the efficiencyof image transmission but also introduce the high security of the chaotic system. Specifically, the proposed CCSEcan fully leverage the advantages of the Chebyshev chaotic system and CS, enabling it to withstand various attacks,such as differential attacks, and exhibit robustness. First, we use a sparse trans-form to sparse the plaintext imageand then use theArnold transformto perturb the image pixels. After that,we elaborate aChebyshev Toeplitz chaoticsensing matrix for CCSE. By using this Toeplitz matrix, the perturbed image is compressed and sampled to reducethe transmission bandwidth and the amount of data. Finally, a bilateral diffusion operator and a chaotic encryptionoperator are used to perturb and expand the image pixels to change the pixel position and value of the compressedimage, and ultimately obtain an encrypted image. Experimental results show that our method can be resistant tovarious attacks, such as the statistical attack and noise attack, and can outperform its current competitors.展开更多
A novel visually meaningful image encryption algorithm is proposed based on a hyperchaotic system and compressive sensing(CS), which aims to improve the visual security of steganographic image and decrypted quality. F...A novel visually meaningful image encryption algorithm is proposed based on a hyperchaotic system and compressive sensing(CS), which aims to improve the visual security of steganographic image and decrypted quality. First, a dynamic spiral block scrambling is designed to encrypt the sparse matrix generated by performing discrete wavelet transform(DWT)on the plain image. Then, the encrypted image is compressed and quantified to obtain the noise-like cipher image. Then the cipher image is embedded into the alpha channel of the carrier image in portable network graphics(PNG) format to generate the visually meaningful steganographic image. In our scheme, the hyperchaotic Lorenz system controlled by the hash value of plain image is utilized to construct the scrambling matrix, the measurement matrix and the embedding matrix to achieve higher security. In addition, compared with other existing encryption algorithms, the proposed PNG-based embedding method can blindly extract the cipher image, thus effectively reducing the transmission cost and storage space. Finally, the experimental results indicate that the proposed encryption algorithm has very high visual security.展开更多
As the amount of data produced by ground penetrating radar （GPR） for roots is large, the transmission and the storage of data consumes great resources. To alleviate this problem, we propose here a root imaging algor...As the amount of data produced by ground penetrating radar （GPR） for roots is large, the transmission and the storage of data consumes great resources. To alleviate this problem, we propose here a root imaging algorithm using chaotic particle swarm optimal （CPSO） compressed sensing based on GPR data according to the sparsity of root space. Radar data are decomposed, observed, measured and represented in sparse manner, so roots image can be reconstructed with limited data. Firstly, radar signal measurement and sparse representation are implemented, and the solution space is established by wavelet basis and Gauss random matrix; secondly, the matching function is considered as the fitness function, and the best fitness value is found by a PSO algorithm; then, a chaotic search was used to obtain the global optimal operator; finally, the root image is reconstructed by the optimal operators. A-scan data, B-scan data, and complex data from American GSSI GPR is used, respectively, in the experimental test. For B-scan data, the computation time was reduced 60 % and PSNR was improved 5.539 dB; for actual root data imaging, the reconstruction PSNR was 26.300 dB, and total computation time was only 67.210 s. The CPSO-OMP algorithm overcomes the problem of local optimum trapping and comprehensively enhances the precision during reconstruction.展开更多
Based on compressive sensing and fractional discrete cosine transform(DCT)via polynomial interpolation(PI-FrDCT),an image encryption algorithm is proposed,in which the compression and encryption of an image are accomp...Based on compressive sensing and fractional discrete cosine transform(DCT)via polynomial interpolation(PI-FrDCT),an image encryption algorithm is proposed,in which the compression and encryption of an image are accomplished simultaneously.It can keep information secret more effectively with low data transmission.Three-dimensional piecewise and nonlinear chaotic maps are employed to obtain a generating sequence and the exclusive OR(XOR)matrix,which greatly enlarge the key space of the encryption system.Unlike many other fractional transforms,the output of PI-FrDCT is real,which facilitates the storage,transmission and display of the encrypted image.Due to the introduction of a plain-image-dependent disturbance factor,the initial values and system parameters of the encryption scheme are determined by cipher keys and plain-image.Thus,the proposed encryption scheme is very sensitive to the plain-image,which makes the encryption system more secure.Experimental results demonstrate the validity and the reliability of the proposed encryption algorithm.展开更多
In the Digital World scenario,the confidentiality of information in video transmission plays an important role.Chaotic systems have been shown to be effective for video signal encryption.To improve video transmission ...In the Digital World scenario,the confidentiality of information in video transmission plays an important role.Chaotic systems have been shown to be effective for video signal encryption.To improve video transmission secrecy,compressive encryption method is proposed to accomplish compression and encryption based on fractional order hyper chaotic system that incorporates Compressive Sensing(CS),pixel level,bit level scrambling and nucleotide Sequences operations.The measurement matrix generates by the fractional order hyper chaotic system strengthens the efficiency of the encryption process.To avoid plain text attack,the CS measurement is scrambled to its pixel level,bit level scrambling decreases the similarity between the adjacent measurements and the nucleotide sequence operations are done on the scrambled bits,increasing the encryption.Two stages are comprised in the reconstruction technique,the first stage uses the intra-frame similarity and offers robust preliminary retrieval for each frame,and the second stage iteratively improves the efficiency of reconstruction by integrating inter frame Multi Hypothesis(MH)estimation and weighted residual sparsity modeling.In each iteration,the residual coefficient weights are modified using a mathematical approach based on the MH predictions,and the Split Bregman iteration algorithm is defined to resolve weighted l1 regularization.Experimental findings show that the proposed algorithm provides good compression of video coupled with an efficient encryption method that is resistant to multiple attacks.展开更多
混沌压缩感知是一种利用混沌系统实现非线性测量,通过混沌脉冲同步和参数估计技术实现信号重构的压缩感知理论。针对混沌压缩感知重构系统中采用l1范数正则化信号系数导致在信号稀疏水平较高时重构性能急剧下降的问题,利用lp(0 p 1)范...混沌压缩感知是一种利用混沌系统实现非线性测量,通过混沌脉冲同步和参数估计技术实现信号重构的压缩感知理论。针对混沌压缩感知重构系统中采用l1范数正则化信号系数导致在信号稀疏水平较高时重构性能急剧下降的问题,利用lp(0 p 1)范数来正则化信号系数,将重构系统中的非线性约束l1范数最小化问题替换为非线性约束lp范数最小化问题,并提出-正则迭代再加权非线性最小二乘算法进行求解。以Henon混沌为例,研究了频域稀疏信号的重构性能,数值模拟表明lp范数正则化能够准确重构出比l1范数正则化时稀疏水平更高的信号。展开更多
基金the National Natural Science Foundation of China(Nos.62002028,62102040 and 62202066).
文摘Images are the most important carrier of human information. Moreover, how to safely transmit digital imagesthrough public channels has become an urgent problem. In this paper, we propose a novel image encryptionalgorithm, called chaotic compressive sensing (CS) encryption (CCSE), which can not only improve the efficiencyof image transmission but also introduce the high security of the chaotic system. Specifically, the proposed CCSEcan fully leverage the advantages of the Chebyshev chaotic system and CS, enabling it to withstand various attacks,such as differential attacks, and exhibit robustness. First, we use a sparse trans-form to sparse the plaintext imageand then use theArnold transformto perturb the image pixels. After that,we elaborate aChebyshev Toeplitz chaoticsensing matrix for CCSE. By using this Toeplitz matrix, the perturbed image is compressed and sampled to reducethe transmission bandwidth and the amount of data. Finally, a bilateral diffusion operator and a chaotic encryptionoperator are used to perturb and expand the image pixels to change the pixel position and value of the compressedimage, and ultimately obtain an encrypted image. Experimental results show that our method can be resistant tovarious attacks, such as the statistical attack and noise attack, and can outperform its current competitors.
基金supported by the National Natural Science Foundation of China (Grant No. 61672124)the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund (Grant No. MMJJ20170203)+3 种基金Liaoning Province Science and Technology Innovation Leading Talents Program Project (Grant No. XLYC1802013)Key R&D Projects of Liaoning Province (Grant No. 2019020105JH2/103)Jinan City ‘20 Universities’ Funding Projects Introducing Innovation Team Program (Grant No. 2019GXRC031)Research Fund of Guangxi Key Lab of Multi-source Information Mining & Security (Grant No. MIMS20-M-02)。
文摘A novel visually meaningful image encryption algorithm is proposed based on a hyperchaotic system and compressive sensing(CS), which aims to improve the visual security of steganographic image and decrypted quality. First, a dynamic spiral block scrambling is designed to encrypt the sparse matrix generated by performing discrete wavelet transform(DWT)on the plain image. Then, the encrypted image is compressed and quantified to obtain the noise-like cipher image. Then the cipher image is embedded into the alpha channel of the carrier image in portable network graphics(PNG) format to generate the visually meaningful steganographic image. In our scheme, the hyperchaotic Lorenz system controlled by the hash value of plain image is utilized to construct the scrambling matrix, the measurement matrix and the embedding matrix to achieve higher security. In addition, compared with other existing encryption algorithms, the proposed PNG-based embedding method can blindly extract the cipher image, thus effectively reducing the transmission cost and storage space. Finally, the experimental results indicate that the proposed encryption algorithm has very high visual security.
基金supported by the Fundamental Research Funds for the Central Universities(DL13BB21)the Natural Science Foundation of Heilongjiang Province(C2015054)+1 种基金Heilongjiang Province Technology Foundation for Selected Osverseas ChineseNatural Science Foundation of Heilongjiang Province(F2015036)
文摘As the amount of data produced by ground penetrating radar （GPR） for roots is large, the transmission and the storage of data consumes great resources. To alleviate this problem, we propose here a root imaging algorithm using chaotic particle swarm optimal （CPSO） compressed sensing based on GPR data according to the sparsity of root space. Radar data are decomposed, observed, measured and represented in sparse manner, so roots image can be reconstructed with limited data. Firstly, radar signal measurement and sparse representation are implemented, and the solution space is established by wavelet basis and Gauss random matrix; secondly, the matching function is considered as the fitness function, and the best fitness value is found by a PSO algorithm; then, a chaotic search was used to obtain the global optimal operator; finally, the root image is reconstructed by the optimal operators. A-scan data, B-scan data, and complex data from American GSSI GPR is used, respectively, in the experimental test. For B-scan data, the computation time was reduced 60 % and PSNR was improved 5.539 dB; for actual root data imaging, the reconstruction PSNR was 26.300 dB, and total computation time was only 67.210 s. The CPSO-OMP algorithm overcomes the problem of local optimum trapping and comprehensively enhances the precision during reconstruction.
基金supported by National Natural Science Foundation of China(Nos.61662047 and 61462061).
文摘Based on compressive sensing and fractional discrete cosine transform(DCT)via polynomial interpolation(PI-FrDCT),an image encryption algorithm is proposed,in which the compression and encryption of an image are accomplished simultaneously.It can keep information secret more effectively with low data transmission.Three-dimensional piecewise and nonlinear chaotic maps are employed to obtain a generating sequence and the exclusive OR(XOR)matrix,which greatly enlarge the key space of the encryption system.Unlike many other fractional transforms,the output of PI-FrDCT is real,which facilitates the storage,transmission and display of the encrypted image.Due to the introduction of a plain-image-dependent disturbance factor,the initial values and system parameters of the encryption scheme are determined by cipher keys and plain-image.Thus,the proposed encryption scheme is very sensitive to the plain-image,which makes the encryption system more secure.Experimental results demonstrate the validity and the reliability of the proposed encryption algorithm.
文摘In the Digital World scenario,the confidentiality of information in video transmission plays an important role.Chaotic systems have been shown to be effective for video signal encryption.To improve video transmission secrecy,compressive encryption method is proposed to accomplish compression and encryption based on fractional order hyper chaotic system that incorporates Compressive Sensing(CS),pixel level,bit level scrambling and nucleotide Sequences operations.The measurement matrix generates by the fractional order hyper chaotic system strengthens the efficiency of the encryption process.To avoid plain text attack,the CS measurement is scrambled to its pixel level,bit level scrambling decreases the similarity between the adjacent measurements and the nucleotide sequence operations are done on the scrambled bits,increasing the encryption.Two stages are comprised in the reconstruction technique,the first stage uses the intra-frame similarity and offers robust preliminary retrieval for each frame,and the second stage iteratively improves the efficiency of reconstruction by integrating inter frame Multi Hypothesis(MH)estimation and weighted residual sparsity modeling.In each iteration,the residual coefficient weights are modified using a mathematical approach based on the MH predictions,and the Split Bregman iteration algorithm is defined to resolve weighted l1 regularization.Experimental findings show that the proposed algorithm provides good compression of video coupled with an efficient encryption method that is resistant to multiple attacks.
文摘混沌压缩感知是一种利用混沌系统实现非线性测量,通过混沌脉冲同步和参数估计技术实现信号重构的压缩感知理论。针对混沌压缩感知重构系统中采用l1范数正则化信号系数导致在信号稀疏水平较高时重构性能急剧下降的问题,利用lp(0 p 1)范数来正则化信号系数,将重构系统中的非线性约束l1范数最小化问题替换为非线性约束lp范数最小化问题,并提出-正则迭代再加权非线性最小二乘算法进行求解。以Henon混沌为例,研究了频域稀疏信号的重构性能,数值模拟表明lp范数正则化能够准确重构出比l1范数正则化时稀疏水平更高的信号。
