Parallel Mixed Image Encryption and Extraction Algorithm Based on Compressed Sensing

In the actual image processing process, we often encounter mixed images that contain multiple valid messages. Such images not only need to be transmitted safely, but also need to be able to achieve effective separation at the receiving end. This paper designs a secure and efficient encryption and separation algorithm based on this kind of mixed image. Since chaotic system has the characteristics of initial sensitivity and pseudo-randomness, a chaos matrix is introduced into the compressed sensing framework. By using sequence signal to adjust the chaotic system, the key space can be greatly expanded. In the algorithm, we take the way of parallel transmission to block the data. This method can realize the efficient calculation of complex tasks in the image encryption system and improve the data processing speed. In the decryption part, the algorithm in this paper can not only realize the restoration of images, but also complete the effective separation of images through the improved restoration algorithm.

[1]  Hao Ye,et al.  The construction of measurement matrices based on block weighing matrix in compressed sensing , 2016, Signal Process..

[2]  Chengzhi Deng,et al.  An image compression and encryption algorithm based on chaotic system and compressive sensing , 2019, Optics & Laser Technology.

[3]  Lisheng Xu,et al.  Exploiting chaos-based compressed sensing and cryptographic algorithm for image encryption and compression , 2018 .

[4]  Avid Avokh,et al.  On the performance of sink placement in WSNs considering energy-balanced compressive sensing-based data aggregation , 2018, J. Netw. Comput. Appl..

[5]  Erfu Wang,et al.  Parallel Encryption of Noisy Images Based on Sequence Generator and Chaotic Measurement Matrix , 2020, Complex..

[6]  Miguel Angel Murillo-Escobar,et al.  Suggested Integral Analysis for Chaos-Based Image Cryptosystems , 2019, Entropy.

[7]  Zhenjun Tang,et al.  Multiple-image encryption with bit-plane decomposition and chaotic maps , 2016 .

[8]  Sid-Ali Addouche,et al.  A novel robust compression-encryption of images based on SPIHT coding and fractional-order discrete-time chaotic system , 2019, Optics & Laser Technology.

[9]  Zhihong Zhou,et al.  Image compression–encryption scheme based on hyper-chaotic system and 2D compressive sensing , 2016 .

[10]  Richie Gao,et al.  A novel track control for Lorenz system with single state feedback , 2019, Chaos, Solitons & Fractals.

[11]  Julien Clinton Sprott,et al.  Recent new examples of hidden attractors , 2015 .

[12]  Haibo Jiang,et al.  A New Class of Three-Dimensional Maps with Hidden Chaotic Dynamics , 2016, Int. J. Bifurc. Chaos.

[13]  Yang Li,et al.  Optical image encryption technique based on compressed sensing and Arnold transformation , 2013 .

[14]  Azam Karami,et al.  Compression and noise reduction of hyperspectral images using non-negative tensor decomposition and compressed sensing , 2016 .

[15]  Yong Wang,et al.  An image coding scheme using parallel compressive sensing for simultaneous compression-encryption applications , 2017, J. Vis. Commun. Image Represent..

[16]  Chengzhi Deng,et al.  Image compression-encryption algorithms by combining hyper-chaotic system with discrete fractional random transform , 2018, Optics & Laser Technology.

[17]  Hejiao Huang,et al.  2D Logistic-Sine-coupling map for image encryption , 2018, Signal Process..

[18]  R. Parvaz,et al.  A fast multiple-image encryption algorithm based on hybrid chaotic systems for gray scale images , 2019, Optik.

[19]  Sen Bai,et al.  Robust and hierarchical watermarking of encrypted images based on Compressive Sensing , 2016, Signal Process. Image Commun..

[20]  V.K. Goyal,et al.  Compressive Sampling and Lossy Compression , 2008, IEEE Signal Processing Magazine.

[21]  Xing-yuan Wang,et al.  A fast image algorithm based on rows and columns switch , 2014, Nonlinear Dynamics.

[22]  Wenhong Wang,et al.  A Novel Image Compression-Encryption Scheme Based on Chaos and Compression Sensing , 2018, IEEE Access.

[23]  Jian Li,et al.  Image compression-encryption scheme based on fractional order hyper-chaotic systems combined with 2D compressed sensing and DNA encoding , 2019, Optics & Laser Technology.

[24]  Jianhao Hu,et al.  A New Plaintext-Related Image Encryption Scheme Based on Chaotic Sequence , 2019, IEEE Access.

[25]  Yiran Chen,et al.  A color image cryptosystem based on dynamic DNA encryption and chaos , 2019, Signal Process..

[26]  Jian Liu,et al.  A novel simple chaotic circuit based on memristor–memcapacitor , 2020 .

[27]  Hassan Ghassemian,et al.  Remote Sensing Image Fusion Using Ripplet Transform and Compressed Sensing , 2015, IEEE Geoscience and Remote Sensing Letters.

[28]  Shuzhen Chen,et al.  Compressed sensing magnetic resonance imaging based on dictionary updating and block-matching and three-dimensional filtering regularisation , 2016, IET Image Process..

[29]  John Wawrzynek,et al.  Compressive sensing and sparse antenna arrays for indoor 3-D microwave imaging , 2017, 2017 25th European Signal Processing Conference (EUSIPCO).

[30]  Seiichi Uchida,et al.  A parallel image encryption method based on compressive sensing , 2012, Multimedia Tools and Applications.

[31]  Dolendro Singh Laiphrakpam,et al.  Multiple images encryption based on 3D scrambling and hyper-chaotic system , 2021, Inf. Sci..

[32]  Meng Li,et al.  A visually secure image encryption scheme based on semi-tensor product compressed sensing , 2020, Signal Process..

[33]  Xuesong Wang,et al.  Multiple-image encryption algorithm based on mixed image element and chaos , 2017, Comput. Electr. Eng..

[34]  G. Leonov,et al.  Hidden attractors in dynamical systems , 2016 .

[35]  Erfu Wang,et al.  Image Parallel Encryption Technology Based on Sequence Generator and Chaotic Measurement Matrix , 2020, Entropy.

[36]  Qun Zhang,et al.  A Novel Motion Compensating Method for MIMO-SAR Imaging Based on Compressed Sensing , 2015, IEEE Sensors Journal.

[37]  Jian Liu,et al.  Characteristic analysis of the fractional-order hyperchaotic complex system and its image encryption application , 2020, Signal Process..

[38]  Shouzhi Yang,et al.  Colour image encryption based on logistic mapping and double random-phase encoding , 2017, IET Image Process..