Single-pixel imaging (SPI) techniques acquire one-dimensional (1-D) intensities from different projections of the object. Applying SPI to object authentication with optical encryption has the advantages of high security and easy transmission. However, previous image-based schemes have the problem of taking long time to reconstruct image from a large number of measurements. What’s more, perfect reconstruction is not necessary for object authentication. We propose an imageless object authentication strategy using single-pixel detection and sub-Nyquist sampling of Fourier spectrum coefficients. The method consists of three steps: encoding, four-step phase-shifting and authentication. First, we conduct SPI to encode image to 1-D intensities with Fourier basis patterns. Second, we use four-step phase-shifting method to get the Fourier transform of the object (i.e., Fourier spectrum) instead of image reconstruction. Third, calculate the correlation extent between the object and the reference image and then visualize it as a map. If there is only one area that is much higher than other places in the map, the similarity between the image and the reference is high. We have verified the effectiveness of this method by adding noise in simulation. When adding noise or performing at low sampling rate, our scheme still realizes accurate authentication.
Single-pixel imaging (SPI) techniques acquire one-dimensional (1-D) intensities from different projections of the object. Applying SPI to object authentication with optical encryption has the advantages of high security and easy transmission. However, previous image-based schemes have the problem of taking long time to reconstruct image from a large number of measurements. What’s more, perfect reconstruction is not necessary for object authentication. We propose an imageless object authentication strategy using single-pixel detection and sub-Nyquist sampling of Fourier spectrum coefficients. The method consists of three steps: encoding, four-step phase-shifting and authentication. First, we conduct SPI to encode image to 1-D intensities with Fourier basis patterns. Second, we use four-step phase-shifting method to get the Fourier transform of the object (i.e., Fourier spectrum) instead of image reconstruction. Third, calculate the correlation extent between the object and the reference image and then visualize it as a map. If there is only one area that is much higher than other places in the map, the similarity between the image and the reference is high. We have verified the effectiveness of this method by adding noise in simulation. When adding noise or performing at low sampling rate, our scheme still realizes accurate authentication.
In the rapidly evolving field of optical information security, single-pixel imaging (SPI) has emerged as a promising technique for hidden information transmission. However, traditional SPI methods face significant challenges, including the need for excessive modulation patterns and the vulnerability of encrypted information during transmission. Furthermore, the field lacks efficient methods to reconstruct both plaintext and ciphertext images from the same set of single-pixel measurements. Here, we propose a novel and efficient encryption strategy for Fourier single-pixel imaging (FSPI) that addresses these critical challenges. Our approach integrates two key innovations: a two-step Fourier-total variation conjugate gradient descent (F-TVCGD) method and a dual-key decryption mechanism. The F-TVCGD method significantly reduces the number of modulation patterns required for image reconstruction, enhancing efficiency and minimizing data redundancy. Our dual-key mechanism enables the reconstruction of both plaintext and ciphertext images from a single set of single-pixel measurements using different decryption keys, significantly enhancing security without compromising efficiency. The incorporation of Fourier symmetric patterns improves the convergence robustness of the symmetric gradient descent (SGD) algorithm, leading to superior performance under challenging conditions such as sparse sampling and noise attacks. Numerical simulations and optical experiments validate our method's improvements in both accuracy and security compared to traditional approaches. Our findings demonstrate that the proposed F-TVCGD and SGD strategies effectively address the challenges of excessive modulation patterns and information vulnerability in FSPI.
As a promising technique, the spatial information of an object can be acquired by employing active illumination of sinusoidal patterns in the Fourier single-pixel imaging. However, the major challenge in this field is that a large number of illumination patterns should be generated to record measurements in order to avoid the loss of object details. In this paper, an optical multiple-image authentication method is proposed based on sparse sampling and multiple logistic maps. To improve the measurement efficiency, object images to be authenticated are randomly sampled based on the spatial frequency distribution with smaller size, and the Fourier sinusoid patterns generated for each frequency are converted into binarized illumination patterns using the Floyd-Steinberg error diffusion dithering algorithm. In the generation process of the ciphertext, two chaotic sequences are used to randomly select spatial frequency for each object image and scramble all measurements, respectively. Considering initial values and bifurcation parameters of logistic maps as secret keys, the security of the cryptosystem can be greatly enhanced. For the first time to our knowledge, how to authenticate the reconstructed object image is implemented using a significantly low number of measurements (i.e., at a very low sampling ratio less than 5% of Nyquist limit) in the Fourier single-pixel imaging. The experimental results as well as simulations illustrate the feasibility of the proposed multiple-image authentication mechanism, which can provide an effective alternative for the related research.
An optical image encryption method is proposed based on Fourier single-pixel imaging and iterated phase retrieval algorithm. First, a binary barcode image containing two groups of horizontal strips is randomly generated and used as the target image in the single-pixel imaging process. Second, considering the barcode image as the amplitude constraint, the original plaintext image is encoded to two phase-only masks using a designed phase retrieval algorithm in Fresnel domain, and these masks are applied as secret keys. Finally, the barcode image is encrypted to a series of measurements using two-step phase shift Fourier single-pixel imaging as the ciphertext. Differing other methods, the original image is not directly imaged and encoded into the ciphertext. Even the ciphertext is obtained by a cracker, only the barcode image may be further discovered. Due to two phase-only masks as secret keys, the security level of the cryptosystem can be enhanced greatly. The simulated results verify the feasibility of the proposed method, and this work provides an effective alternative for the related research.
Single-pixel imaging (SPI) enables an invisible target to be imaged onto a photosensitive surface without a lens, emerging as a promising way for indirect optical encryption. However, due to its linear and broadcast imaging principles, SPI encryption has been confined to a single-user framework for the long term. We propose a multi-image SPI encryption method and combine it with orthogonal frequency division multiplexing-assisted key management, to achieve a multiuser SPI encryption and authentication framework. Multiple images are first encrypted as a composite intensity sequence containing the plaintexts and authentication information, simultaneously generating different sets of keys for users. Then, the SPI keys for encryption and authentication are asymmetrically isolated into independent frequency carriers and encapsulated into a Malus metasurface, so as to establish an individually private and content-independent channel for each user. Users can receive different plaintexts privately and verify the authenticity, eliminating the broadcast transparency of SPI encryption. The improved linear security is also verified by simulating attacks. By the combination of direct key management and indirect image encryption, our work achieves the encryption and authentication functionality under a multiuser computational imaging framework, facilitating its application in optical communication, imaging, and security.
Single-pixel imaging (SPI) can transform 2D or 3D image data into 1D light signals, which offers promising prospects for image compression and transmission. However, during data communication these light signals in public channels will easily draw the attention of eavesdroppers. Here, we introduce an efficient encryption method for SPI data transmission that uses the 3D Arnold transformation to directly disrupt 1D single-pixel light signals and utilizes the elliptic curve encryption algorithm for key transmission. This encryption scheme immediately employs Hadamard patterns to illuminate the scene and then utilizes the 3D Arnold transformation to permutate the 1D light signal of single-pixel detection. Then the transformation parameters serve as the secret key, while the security of key exchange is guaranteed by an elliptic curve-based key exchange mechanism. Compared with existing encryption schemes, both computer simulations and optical experiments have been conducted to demonstrate that the proposed technique not only enhances the security of encryption but also eliminates the need for complicated pattern scrambling rules. Additionally, this approach solves the problem of secure key transmission, thus ensuring the security of information and the quality of the decrypted images.
We propose a steganographic optical image encryption based on single-pixel imaging (SPI) and an untrained neural network. In this encryption scheme, random binary illumination patterns are projected onto a secret image and light intensities reflected from the image are then detected by a bucket detector (BD). To enhance the security of collected secret data, a steganographic approach is introduced in this method, which implements data hiding with a SPI system using encoded illumination patterns. A non-secret image is illuminated with a sequence of encoded patterns that were generated from the scrambled measurements of secret image, and sequential cyphertext data can be obtained by collecting the diffraction data with the BD. Different from traditional SPI-based encryption schemes, an untrained neural network is adopted as a SPI-encrypted image processor, which allows to reduce time spent on data preparation and reconstruct the secret images with high quality. Both computer simulations and optical experiments are carried out to demonstrate the feasibility of the method.