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.
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.
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.
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) 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.
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.
Providing secure and efficient transmission for multiple optical images has been an important issue in the field of information security. Here we present a hybrid image compression, encryption and reconstruction scheme based on deep learning-assisted single-pixel imaging (SPI) and orthogonal coding. In the optical SPI-based encryption, two-dimensional images are encrypted into one-dimensional bucket signals, which will be further compressed by a binarization operation. By overlaying orthogonal coding on the compressed signals, we obtain the ciphertext that allows multiple users to access with the same privileges. The ciphertext can be decoded back to the binarized bucket signals with the help of orthogonal keys. To enhance reconstruction efficiency and quality, a deep learning framework based on DenseNet is employed to retrieve the original optical images. Numerical and experimental results have been presented to verify the feasibility and effectiveness of the proposed scheme.
Multi-object optical encryption has emerged as a promising field for enhancing encryption performance and reducing communication overhead, which can ensure the security of single-pixel imaging. However, it faces some critical challenges like low efficiency, reliance on complex system design, high hardware costs, and the difficulty of parallel encryption with independent decryption, hindering practical deployment. In this work, an illumination pattern construction algorithm is proposed to generate projected basis patterns for parallel optical encryption, while a decoupling algorithm is developed to demodulate coupled measurements to recover Hadamard spectrum for each object. Independent decryption is then performed using a random-order Hadamard matrix assigned to each object. The proposed method achieves multi-object parallel encryption and independent decryption using a lightweight optical system, with improved efficiency, lower hardware costs, and smaller ciphertext size compared to conventional methods. In addition, it also exhibits robustness against both cropping and noise attacks. These results indicate potential for practical applications and may contribute to future developments in multi-object optical encryption for single-pixel imaging security.