High performance optical encryption based on computational ghost imaging with QR code and compressive sensing technique

Zhao, Shengmei; Wang, Le; Liang, Wenfeng; Cheng, Wei‐Wen; Gong, Lei

doi:10.1016/j.optcom.2015.04.063

Cited by 122 publications

(39 citation statements)

References 26 publications

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“…Fourier transform patterns [26], Hadamard patterns [8], wavelet patterns [27]). In addition, error correction coding ( [28][29][30]) can be used to improve the imaging efficiency in encrypted SPI. However, it is still hard to successfully recover an object image with good fidelity from only a short single-pixel intensity sequence consisting of a small number of pixels.…”

Section: Introductionmentioning

confidence: 99%

Fast object classification in single-pixel imaging

Jiao¹

2018

Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018)

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In single-pixel imaging (SPI), the target object is illuminated with varying patterns sequentially and an intensity sequence is recorded by a single-pixel detector without spatial resolution. A high quality object image can only be computationally reconstructed after a large number of illuminations, with disadvantages of long imaging time and high cost. Conventionally, object classification is performed after a reconstructed object image with good fidelity is available. In this paper, we propose to classify the target object with a small number of illuminations in a fast manner for Fourier SPI. A naive Bayes classifier is employed to classify the target objects based on the single-pixel intensity sequence without any image reconstruction and each sequence element is regarded as an object feature in the classifier. Simulation results demonstrate our proposed scheme can classify the number digit object images with high accuracy (e.g. 80% accuracy using only 13 illuminations, at a sampling ratio of 0.3%).

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Section: Introductionmentioning

confidence: 99%

Fast object classification in single-pixel imaging

Jiao¹

2018

Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018)

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“…The key sensitivity of measurement matrices with 3D Lorenz has been analyzed in detail to demonstrate their advantages [15, 24–26]. Here we emphasize the key sensitivity of the order of the tensor product.…”

Section: Numerical Simulation Resultsmentioning

confidence: 99%

Simultaneous encryption and compression of medical images based on optimized tensor compressed sensing with 3D Lorenz

et al. 2016

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BackgroundThe existing techniques for simultaneous encryption and compression of images refer lossy compression. Their reconstruction performances did not meet the accuracy of medical images because most of them have not been applicable to three-dimensional (3D) medical image volumes intrinsically represented by tensors.MethodsWe propose a tensor-based algorithm using tensor compressive sensing (TCS) to address these issues. Alternating least squares is further used to optimize the TCS with measurement matrices encrypted by discrete 3D Lorenz.ResultsThe proposed method preserves the intrinsic structure of tensor-based 3D images and achieves a better balance of compression ratio, decryption accuracy, and security. Furthermore, the characteristic of the tensor product can be used as additional keys to make unauthorized decryption harder.ConclusionsNumerical simulation results verify the validity and the reliability of this scheme.

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“…Meanwhile, various optical transforms such as fractional Fourier transform, Fresnel transform, gyrator transform, and other means have been applied, where additional parameters can be considered the secret keys to enhance the level of security [16][17][18][19][20][21][22][23][24][25][26][27][28]. Due to its novel physical characteristics such as the complexity of its optical parameters, the ghost imaging technique can provide a promising alternative for the optical cryptosystem [29][30][31][32][33]. Zhang et al [34] encrypted a fast Fourier transformed image using the compressive ghost imaging system to improve the level of security.…”

Section: Introductionmentioning

confidence: 99%

Optical image encryption via high-quality computational ghost imaging using iterative phase retrieval

Sui

Cheng

et al. 2018

Laser Phys. Lett.

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A novel computational ghost imaging scheme based on specially designed phase-only masks, which can be efficiently applied to encrypt an original image into a series of measured intensities, is proposed in this paper. First, a Hadamard matrix with a certain order is generated, where the number of elements in each row is equal to the size of the original image to be encrypted. Each row of the matrix is rearranged into the corresponding 2D pattern. Then, each pattern is encoded into the phase-only masks by making use of an iterative phase retrieval algorithm. These specially designed masks can be wholly or partially used in the process of computational ghost imaging to reconstruct the original information with high quality. When a significantly small number of phase-only masks are used to record the measured intensities in a single-pixel bucket detector, the information can be authenticated without clear visualization by calculating the nonlinear correlation map between the original image and its reconstruction. The results illustrate the feasibility and effectiveness of the proposed computational ghost imaging mechanism, which will provide an effective alternative for enriching the related research on the computational ghost imaging technique.

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High performance optical encryption based on computational ghost imaging with QR code and compressive sensing technique

Cited by 122 publications

References 26 publications

Fast object classification in single-pixel imaging

Fast object classification in single-pixel imaging

Simultaneous encryption and compression of medical images based on optimized tensor compressed sensing with 3D Lorenz

Optical image encryption via high-quality computational ghost imaging using iterative phase retrieval

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