An optical multiple-image authentication based on computational ghost imaging and total-variation minimization

We provide a method to evaluate effects of a lossy and noisy optical channel in computational ghost imaging (CGI) technique. Instead of preparing an external noise source, we simulate the optical channel with a basic CGI experiment using programmatically generated noise-induced patterns. By using our method, we show that CGI can reject a noise of which intensity is similar with an imaging signal intensity at a target. The results with our method are well matched with experimental ones including external noise source. This method would provide useful knowledge to analyze environmental effects in CGI without realization of the environment.

Recent researches showed that the traditional ghost imaging (TGI) using pseudo-thermal light can be affected by the solid scattering material placed between the object and the light source. This scattering case might also affect the computational ghost imaging (CGI) and is considered in this paper. Different from the TGI system modeled by Huygens–Fresnel theory in continuous coordinates, in CGI the use of computer-generated patterns with the controllable size ( $d$ ) of each pixel discretizes the object space into the $d$ -based pixel-grids. Therefore, how the CGI system is affected by the scatters depends on the distribution of the scattered light on these discretized grids instead of in continuous coordinates, which has not been explored. In this paper, we demonstrate that the “anti-scattering” capacity of CGI is governed by the discrete point-scattering-function (DPSF) that is determined by $\frac{{w_{0}}}{d}$ ( $w_{0}$ : the width of point-scattering-function of the scatters). We show that the blurry effect on the reconstructed image is visible as $d\ll\frac{{w_{0}}}{2}$ , but can be highly restrained as $d$ increasing to be comparable to $\frac{w_{0}}{2}$ or larger. Furthermore, $d$ determines the spatial resolution power of CGI. In the given CGI system, the minimum $d$ of $\sim\frac{{w}_{0}}{5}$ could be achieved with maintaining the behavior of “scattering-free”.

The non‐local imaging characteristics of computational ghost imaging (CGI) make it widely used in the field of information security. However, the information processing method based on traditional CGI has some problems in the process of multi‐image encryption, such as low efficiency and unsatisfactory reconstruction quality. Therefore, this article proposes to use wavelet transform and singular value decomposition technology to help computational ghost imaging to efficiently complete the coding and encryption of multiple images, and use alternating direction multiplier method (ADMM) in the process of image restoration to carry out high‐quality reconstruction of the original encrypted image. The results show that the scheme has good reconstruction effect, strong security and robustness even at a low sampling rate. It provides some reference for digital watermarking technology and cryptography.

An interpolation computational ghost imaging (ICGI) method is proposed and demonstrated that is able to reduce the noise interference from a fluctuating source and background. The noise is estimated through periodic illuminations by a specific assay pattern during sampling, which is then used to correct the bucket detector signal. To validate this method simulations and experiments were conducted. Light source intensity and background lighting were randomly varied to modulate the noise. The results show that good quality images can be obtained, while with conventional computational ghost imaging (CGI) the reconstructed object is barely recognizable. The ICGI method offers a general approach applicable to all CGI techniques, which can attenuate the interference from source fluctuations, background light noise, dynamic scattering, and so on.

Single-pixel imaging uses a single-pixel detector, rather than a focal plane detector array, to image a scene. It provides advantages for applications such as multi-wavelength, three-dimensional imaging. However, low frame rates have been a major obstacle inhibiting the use of computational ghost imaging technique in wider applications since its invention one decade ago. To address this problem, a computational ghost imaging scheme, which utilizes an LED-based, high-speed illumination module is presented in this work. At 32 × 32 pixel resolution, the proof-of-principle system achieved continuous imaging with 1000 fps frame rate, approximately two orders larger than those of other existing ghost imaging systems. The proposed scheme provides a cost-effective and high-speed imaging technique for dynamic imaging applications.

Ghost imaging has gone through from quantum to classical pseudothermal to computational field over the last two decades. As a kernel part in computational ghost imaging (CGI), the reconstruction algorithm plays a decisive role in imaging quality and system practicality. In order to introduce more prior knowledge into the reconstruction algorithm, existing research adds image patch prior into CGI and improves the imaging efficiency. In this paper, the total variation minimization algorithm via adaptive deep dictionary learning (TVADDL) is proposed to update an adaptive deep dictionary through the CGI reconstruction process. The proposed algorithm framework is able to capture more precise texture features with a multi-layer architecture dictionary and adapt the learned dictionary by gradient descent on CGI reconstruction loss value. The results of simulation and experiment show that TVADDL can achieve higher peak signal-to-noise ratio than the algorithms without patch prior and the algorithms using the shallow dictionary or non-adaptive deep dictionary.

To achieve high capacity, high speed, and secure image transmission, we propose a multi-image computational ghost imaging (CGI)-based encryption scheme that integrates compressed sensing (CS), block scrambling, and dynamic-salt-driven bidirectional XOR diffusion. First, multiple images are partitioned into 8 × 8 pixel blocks, and their spatial structure is disrupted through random scrambling. The scrambled composite image then undergoes pixel-level encryption via two-round bidirectional XOR diffusion, using session-unique keys derived from SHA-256-based dynamic salt, eliminating the statistical characteristics of the original images. Subsequently, each pixel block is subjected to both Gaussian CS and Hadamard-based CGI measurements in parallel, achieving dual-mode compressive encryption and enhancing robustness through measurement redundancy. Finally, only the scrambling key, the XOR-diffusion key, and the compressed measurements are stored; the original image information is thus transformed into unrecognizable measurement data. During the decryption process, the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) with a Discrete Cosine Transform (DCT) sparse basis is employed for dual-sparse reconstruction from the compressed measurements, recovering the encrypted composite image. An inverse XOR operation is then applied to remove the pixel-level diffusion, followed by block reordering using the scrambling key to restore the original images. Experimental results demonstrate that the proposed scheme enables efficient and secure multi-image transmission while maintaining high decrypted image quality. Security analysis indicates that the scheme possesses high key sensitivity, effectively resisting chosen-plaintext attacks. Histogram uniformity analysis and cropping attack resistance experiments further confirm its excellent statistical security and robustness.

Edge detection based on computational ghost imaging with structured illuminations

Effect of the ratio of black speckle on computational ghost imaging

Attack techniques on a cryptosystem include not only cryptanalysis, but also forgery and modification of messages, deception and confusion on both sender and receiver sides, and so on. In this Letter, we show that an optical encryption system based on computational ghost imaging (CGI) has security vulnerability owing to its high tolerance for error deviation of ciphertext. It leaves a chance for a forgery attack in which attackers can forge a set of fake keys according to the intercepted ciphertext. If the forged key can be transmitted to the receiver by some disguised means, he/she may be cheated or confused by the retrieved fake images. The discovery of this vulnerability may also help upgrade the CGI-based encryption system.

High Quality 4-dimensional Cone Beam CT by Deforming Prior Images

The influence of uneven temperature distribution on imaging quality of computational ghost imaging (CGI) in the underwater environment is investigated experimentally. It is shown that as the water temperature increases, imaging quality presents a trend from deterioration to improvement. The results can be explained by the changes of the temperature difference between the upper and lower layers of underwater environment and laser spot travelling through the underwater environment. Moreover, the effect from different positions of the underwater environment with the same water temperature on CGI is also discussed.

Anti-scattering medium computational ghost imaging with modified Hadamard patterns

Demonstration of computational ghost imaging through fog

Deep-learning denoising computational ghost imaging