Exploiting optical chaos for double images encryption with compressive sensing and double random phase encoding

Xiao, Jiang; Xiao, Ying; Xie, Yiyuan; Liu, Bocheng; Ye, Yichen; Song, Tingting; Chai, Junxiong; Liu, Yong

doi:10.1016/j.optcom.2020.126683

Cited by 34 publications

(9 citation statements)

References 38 publications

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“…Table 2 shows the PSNR results of different images under different compression ratios, as well as comparisons with references. From Table 2 , we can see that our reconstruction effect is significantly better than the reference [ 7 , 21 , 22 ].…”

Section: Simulation Results and Analysismentioning

confidence: 90%

Multi-Image Compression–Encryption Algorithm Based on Compressed Sensing and Optical Encryption

Wei

Zhang

Tong

2022

Entropy

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In order to achieve large-capacity, fast and secure image transmission, a multi-image compression–encryption algorithm based on two-dimensional compressed sensing (2D CS) and optical encryption is proposed in this paper. Firstly, the paper uses compressed sensing to compress and encrypt multiple images simultaneously, and design a new structured measurement matrix. Subsequently, double random phase encoding based on the multi-parameter fractional quaternion Fourier transform is used to encrypt the multiple images for secondary encryption, which improves the security performance of the images. Moreover, a fractional-order chaotic system with more complex chaotic behavior is constructed for image compression and encryption. Experimental results show that the algorithm has strong robustness and security.

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Section: Simulation Results and Analysismentioning

confidence: 90%

Multi-Image Compression–Encryption Algorithm Based on Compressed Sensing and Optical Encryption

Wei

Zhang

Tong

2022

Entropy

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“…References [ 11 , 12 ] use carrier images transformed by wavelet packets to hide information. References [ 13 , 14 ] proposed an image hiding algorithm in the discrete Fourier transform domain. References [ 15 , 16 ] proposed a DCT algorithm to change the pixel length to achieve image hiding.…”

Section: Related Workmentioning

confidence: 99%

Random Matrix Transformation and Its Application in Image Hiding

Wang

Tan

Yuan

2023

Sensors

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Image coding technology has become an indispensable technology in the field of modern information. With the vigorous development of the big data era, information security has received more attention. Image steganography is an important method of image encoding and hiding, and how to protect information security with this technology is worth studying. Using a basis of mathematical modeling, this paper makes innovations not only in improving the theoretical system of kernel function but also in constructing a random matrix to establish an information-hiding scheme. By using the random matrix as the reference matrix for secret-information steganography, due to the characteristics of the random matrix, the secret information set to be retrieved is very small, reducing the modification range of the steganography image and improving the steganography image quality and efficiency. This scheme can maintain the steganography image quality with a PSNR of 49.95 dB and steganography of 1.5 bits per pixel and can ensure that the steganography efficiency is improved by reducing the steganography set. In order to adapt to different steganography requirements and improve the steganography ability of the steganography schemes, this paper also proposes an adaptive large-capacity information-hiding scheme based on the random matrix. In this scheme, a method of expanding the random matrix is proposed, which can generate a corresponding random matrix according to different steganography capacity requirements to achieve the corresponding secret-information steganography. Two schemes are demonstrated through simulation experiments as well as an analysis of the steganography efficiency, steganography image quality, and steganography capacity and security. The experimental results show that the latter two schemes are better than the first two in terms of steganography capacity and steganography image quality.

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“…Since optical encryption has many merits, such as parallel computation, fast running speed, and processing data in various transform domains, it attracts wide attention from researchers. Among them, double random phase encoding (DRPE) is an effective method and applied for image encryption [31]. As shown in Fig.…”

Section: Double Random Phase Encodingmentioning

confidence: 99%

Content-adaptive image compression and encryption via optimized compressive sensing with double random phase encoding driven by chaos

Gan

Chai

et al. 2022

Complex Intell. Syst.

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With the advancement of multimedia technology and coming of big data era, the size of image data is significantly increased. However, the traditional image encryption methods cannot solve the emerging problems of efficient compression. To settle with this challenge, an effective content-adaptive image compression and encryption method based on compressive sensing and double random phase encoding (DRPE) is proposed in this paper. The original image is converted to one low-frequency part and three high-frequency parts by DWT and then permutated by sorting-based chaotic sequences. Afterward, a novel measurement matrix optimization algorithm based on adaptive step size is presented to measure the high-frequency components. To enhance the security of the scheme, the DRPE, quantization, and diffusion are successively performed on the complex matrix composed of the shuffled low-frequency component and three measurement value matrices to obtain the cipher image. Logistic-Sine chaotic system is utilized to produce the chaotic keystreams for the encryption process, and its system parameter and initial value are determined by the information entropy of the plain image and external key parameters, so that the proposed cipher can withstand known-plaintext and chosen-plaintext attacks effectively. Numerical experiments demonstrate the effectiveness of the proposed image compression and encryption algorithm.

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Exploiting optical chaos for double images encryption with compressive sensing and double random phase encoding

Cited by 34 publications

References 38 publications

Multi-Image Compression–Encryption Algorithm Based on Compressed Sensing and Optical Encryption

Multi-Image Compression–Encryption Algorithm Based on Compressed Sensing and Optical Encryption

Random Matrix Transformation and Its Application in Image Hiding

Content-adaptive image compression and encryption via optimized compressive sensing with double random phase encoding driven by chaos

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