Compressed ghost imaging based on differential speckle patterns*

Self Cite

Ghost imaging (GI) offers great potential with respect to conventional imaging techniques. However, there are still some obstacles for reconstructing images with high quality, especially in the case the orthogonal measurement matrix is impossible to construct. In this paper, we propose a new scheme based on orthogonaltriangular (QR) decomposition, named QR decomposition ghost imaging (QRGI) to reconstruct a better image with good quality. In the scheme, we can change the randomly non-orthogonal measurement matrix into orthonormal matrix by performing QR decomposition in two cases. (1) When the random measurement matrix is square, it can be first decomposed into an orthogonal matrix Q and an upper triangular matrix R. Then let the off-diagonal values of R equal to 0.0, the diagonal elements of R equal to a constant k, where k is the average of all values of the main diagonal, so the resulting measurement matrix can be obtained. (2) When the random measurement matrix is with full rank, we first compute its transpose, and followed with above QR operation. Finally, the image of the object can be reconstructed by correlating the new measurement matrix and corresponding bucket values. Both experimental and simulation results verify the feasibility of the proposed QRGI scheme. Moreover, the results also show that the proposed QRGI scheme could improve the imaging quality comparing to traditional GI (TGI) and differential GI (DGI). Besides, in comparison with the singular value decomposition ghost imaging (SVDGI), the imaging quality and the reconstruction time by using QRGI are similar to those by using SVDGI, while the computing time (the time-consuming on the light patterns computation) is substantially shortened.

“…Hence, according to the second-order correlation (2C) algorithm, [39] the estimation of 𝑂(x, y) can be obtained by…”

Section: -2mentioning

confidence: 99%

Orthogonal-triangular decomposition ghost imaging

Liu¹,

Wang²,

Zhao³

2022

Self Cite

“…To further eliminate the effect of noise from the bucket detector on the imaging of the periodic moving/state-changed object, differential speckle patterns are constructed according to Refs. [21,30]. The light source illuminates a digital micro-mirror device (DMD), which is controlled by a computer, to produce pairs of speckle patterns.…”

Section: Scheme Descriptionmentioning

confidence: 99%

Imaging a periodic moving/state-changed object with Hadamard-based computational ghost imaging

Guo¹,

Wang²,

Zhao³

2022

Self Cite

We propose a method for imaging a periodic moving/state-changed object based on computational ghost imaging with Hadamard speckle patterns and a slow bucket detector, named PO-HCGI. In the scheme, speckle patterns are produced from a part of each row of a Hadamard matrix. Then, in each cycle, multiple speckle patterns are projected onto the periodic moving/state-changed object, and a bucket detector with a slow sampling rate records the total intensities reflected from the object as one measurement. With a series of measurements, the frames of the moving/state-changed object can be obtained directly by second-order correlation function based on the Hadamard matrix and the corresponding bucket detector measurement results. The experimental and simulation results demonstrate the validity of the PO-HCGI. To the best of our knowledge, PO-HCGI is the first scheme that can image a fast periodic moving/state-changed object by computational ghost imaging with a slow bucket detector.

“…Based on the previous discussion of image encryption algorithms based on CS, it is worth noting that while some algorithms have used CS to achieve efficient image compression, the trade-off is reduced image quality and potential security vulnerabilities in the encryption process. [32][33][34] This has led to a growing interest in designing image encryption algorithms that balance robustness and security. One approach that has gained attention is the use of optical encryption methods, such as the double random-phase encoding algorithm.…”

Section: Introductionmentioning

confidence: 99%

Optical image encryption algorithm based on a new four-dimensional memristive hyperchaotic system and compressed sensing

Long

Jiang

et al. 2023

Some existing image encryption schemes use simple low-dimensional chaotic systems, which makes the algorithms insecure and vulnerable to brute force attacks and cracking. Some algorithms have issues such as weak correlation with plaintext images, poor image reconstruction quality, and low efficiency in transmission and storage. To solve these issues, this paper proposes an optical image encryption algorithm based on a new four-dimensional memristive hyperchaotic system (4-D MHS) and compressed sensing (CS). Firstly, this paper proposes a new 4-D MHS, which has larger key space, richer dynamic behavior and more complex hyperchaotic characteristics. The introduction of CS can reduce the image size and the transmission burden of hardware devices. The introduction of double random phase encoding (DRPE) enables this algorithm has the ability of parallel data processing and multi-dimensional coding space, and the hyperchaotic characteristics of 4-D MHS make up for the nonlinear deficiency of DRPE. Secondly, a construction method of the deterministic chaotic measurement matrix (DCMM) is proposed. Using DCMM can not only save a lot of transmission bandwidth and storage space, but also ensure good quality of reconstructed images. Thirdly, the confusion method and diffusion method proposed are related to plaintext images, which require both four hyperchaotic sequences of 4-D MHS and row and column keys based on plaintext images. The generation process of hyperchaotic sequences is closely related to the hash value of plaintext images. Therefore, this algorithm has high sensitivity to plaintext images. The experimental testing and comparative analysis results show that proposed algorithm has good security and effectiveness.