Multiple-image Encryption and Multiplexing Using a Modified Gerchberg–Saxton Algorithm in Fresnel-transform Domain and Computational Ghost Imaging

Peiming Zhang,Yahui Su,Yiqiang Zhang,Leihong Zhang,Runchu Xu,Kaimin Wang,Dawei Zhang 한국광학회 2023 Current Optics and Photonics Vol.7 No.4

Optical information processing technology is characterized by high speed and parallelism, and the light features short wavelength and large information capacity; At the same time, it has various attributes including amplitude, phase, wavelength and polarization, and is a carrier of multi-dimensional information. Therefore, optical encryption is of great significance in the field of information security transmission, and is widely used in the field of image encryption. For multi-image encryption, this paper proposes a multi-image encryption algorithm based on a modified Gerchberg–Saxton algorithm (MGSA) in the Fresnel-transform domain and computational ghost imaging. First, MGSA is used to realize “one code, one key”; Second, phase function superposition and normalization are used to reduce the amount of ciphertext transmission; Finally, computational ghost imaging is used to improve the security of the whole encryption system. This method can encrypt multiple images simultaneously with high efficiency, simple calculation, safety and reliability, and less data transmission. The encryption effect of the method is evaluated by using correlation coefficient and structural similarity, and the effectiveness and security of the method are verified by simulation experiments.

U 2 Net-based Single-pixel Imaging Salient Object Detection

Leihong Zhang,Zimin Shen,Weihong Lin,Dawei Zhang 한국광학회 2022 Current Optics and Photonics Vol.6 No.5

At certain wavelengths, single-pixel imaging is considered to be a solution that can achieve high quality imaging and also reduce costs. However, achieving imaging of complex scenes is an overheadintensive process for single-pixel imaging systems, so low efficiency and high consumption are the biggest obstacles to their practical application. Improving efficiency to reduce overhead is the solution to this problem. Salient object detection is usually used as a pre-processing step in computer vision tasks, mimicking human functions in complex natural scenes, to reduce overhead and improve efficiency by focusing on regions with a large amount of information. Therefore, in this paper, we explore the implementation of salient object detection based on single-pixel imaging after a single pixel, and propose a scheme to reconstruct images based on Fourier bases and use U 2 Net models for salient object detection.

U²Net-based Single-pixel Imaging Salient Object Detection

Leihong Zhang,Zimin Shen,Weihong Lin(강사),Dawei Zhang 한국광학회 2022 Current Optics and Photonics Vol.6 No.5

At certain wavelengths, single-pixel imaging is considered to be a solution that can achieve high quality imaging and also reduce costs. However, achieving imaging of complex scenes is an overhead-intensive process for single-pixel imaging systems, so low efficiency and high consumption are the biggest obstacles to their practical application. Improving efficiency to reduce overhead is the solution to this problem. Salient object detection is usually used as a pre-processing step in computer vision tasks, mimicking human functions in complex natural scenes, to reduce overhead and improve efficiency by focusing on regions with a large amount of information. Therefore, in this paper, we explore the implementation of salient object detection based on single-pixel imaging after a single pixel, and propose a scheme to reconstruct images based on Fourier bases and use U2Net models for salient object detection.

Research on Multiple-image Encryption Scheme Based on Fourier Transform and Ghost Imaging Algorithm

Zhang, Leihong,Yuan, Xiao,Zhang, Dawei,Chen, Jian Optical Society of Korea 2018 Current Optics and Photonics Vol.2 No.4

A new multiple-image encryption scheme that is based on a compressive ghost imaging concept along with a Fourier transform sampling principle has been proposed. This further improves the security of the scheme. The scheme adopts a Fourier transform to sample the original multiple-image information respectively, utilizing the centrosymmetric conjugation property of the spatial spectrum of the images to obtain each Fourier coefficient in the most abundant spatial frequency band. Based on this sampling principle, the multiple images to be encrypted are grouped into a combined image, and then the compressive ghost imaging algorithm is used to improve the security, which reduces the amount of information transmission and improves the information transmission rate. Due to the presence of the compressive sensing algorithm, the scheme improves the accuracy of image reconstruction.

Research on Camouflaged Encryption Scheme Based on Hadamard Matrix and Ghost Imaging Algorithm

Zhang Leihong,Wang Yang,Ye Hualong,Xu Runchu,Zhang Dawei 한국광학회 2021 Current Optics and Photonics Vol.5 No.6

A camouflaged encryption scheme based on Hadamard matrix and ghost imaging is proposed. In the process of the encryption, an orthogonal matrix is used as the projection pattern of ghost imaging to improve the definition of the reconstructed images. The ciphertext of the secret image is constrained to the camouflaged image. The key of the camouflaged image is obtained by the method of sparse decomposition by principal component orthogonal basis and the constrained ciphertext. The information of the secret image is hidden into the information of the camouflaged image which can improve the security of the system. In the decryption process, the authorized user needs to extract the key of the secret image according to the obtained random sequences. The real encrypted information can be obtained. Otherwise, the obtained image is the camouflaged image. In order to verify the feasibility, security and robustness of the encryption system, binary images and gray-scale images are selected for simulation and experiment. The results show that the proposed encryption system simplifies the calculation process, and also improves the definition of the reconstructed images and the security of the encryption system.

Study of the Key Technology of Ghost Imaging Based on Rosette Scanning

Zhang, Leihong,Kang, Yi,Pan, Zilan,Liang, Dong,Li, Bei,Zhang, Dawei,Ma, Xiuhua Optical Society of Korea 2017 Current Optics and Photonics Vol.1 No.5

Ghost imaging offers great potential, with respect to standard imaging, for imaging objects in optically harsh or noisy environments. It can solve the problems that are difficult to solve by conventional imaging techniques. Recently, it has become a hot topic in quantum optics. In this paper, we propose a scheme for ghost imaging based on rosette scanning, named rosette ghost imaging. Sampling a small area sampling instead of the whole object, the instantaneous field of view of rosette scanning is used as the modulation light field in ghost imaging. This scheme reduces energy loss, the number of samples, and the sampling time, while improving the quality of the reconstructed image.

Study of Spectral Reflectance Reconstruction Based on an Algorithm for Improved Orthogonal Matching Pursuit

Zhang Leihong,Liang Dong,Zhang Dawei,Gao Xiumin,Ma Xiuhua 한국광학회 2016 Current Optics and Photonics Vol.20 No.4

Spectral reflectance is sparse in space, and while the traditional spectral-reconstruction algorithm doesnot make full use of this characteristic sparseness, the compressive sensing algorithm can make full useof it. In this paper, on the basis of analyzing compressive sensing based on the orthogonal matching pursuitalgorithm, a new algorithm based on the Dice matching criterion is proposed. The Dice similarity coefficientis introduced, to calculate the correlation coefficient of the atoms and the residual error, and is used toselect the atoms from a library. The accuracy of Spectral reconstruction based on the pseudo-inversemethod, Wiener estimation method, OMP algorithm, and DOMP algorithm is compared by simulation onthe MATLAB platform and experimental testing. The result is that spectral-reconstruction accuracy basedon the DOMP algorithm is higher than for the other three methods. The root-mean-square error and colordifference decreases with an increasing number of principal components. The reconstruction error decreasesas the number of iterations increases. Spectral reconstruction based on the DOMP algorithm can improvethe accuracy of color-information replication effectively, and high-accuracy color-information reproductioncan be realized.

Increased Circulating CXCL10 in Non-Segmental Vitiligo Concomitant with Autoimmune Thyroid Disease and Alopecia Areata

( Li Zhang ),( Xinya Xu ),( Shujun Chen ),( Yuli Kang ),( Xiuxiu Wang ),( Chengfeng Zhang ),( Leihong Xiang ) 대한피부과학회 2019 Annals of Dermatology Vol.31 No.4

Background: Vitiligo is a common acquired pigmentary disease caused by destruction of epidermal melanocytes in underlying autoimmune response. Few studies have been focused on the role of chemokines in non-segmental vitiligo (NSV) concomitant with autoimmune thyroid disease (AITD) and alopecia areata (AA). Objective: The aim of this study was to determine the best serum biomarker for predictive role in the progression of vitiligo and to evaluate the influence of AA and/or AITD on vitiligo by using the biomarker. Methods: This prospective cohort study recruited 45 NSV patients: 14 without either AITD or AA, 12 with AITD, 11 with AA, and 8 with both AITD and AA. Serum levels of CXCL1, CXCL8, CXCL9, CXCL10, CXCL12, CXCL13, and CXCL16 were analyzed by ELISA. CXCR3 mRNA expression was detected on PBMCs by RT-PCR. Improvement was evaluated using repigmentation scales. Results: Serum CXCL10 levels, along with the expression of CXCR3 mRNA were higher in NSV patients with AITD or AA alone than in those without AITD or AA. Moreover, serum CXCL10 levels, along with the expression of CXCR3 mRNA were higher in NSV patients with both AITD and AA than in those with AITD or AA alone. Poorer repigmentation was observed in NSV patients with both AA and AITD than in those with AA or AITD alone. Conclusion: CXCL10 could be a biomarker to predict the progression of NSV. Dermatologists should pay much attention to those NSV patients concomitant with AITD and/or AA, for comorbidity might lead to more active autoimmune reaction. (Ann Dermatol 31(4) 393∼402, 2019)

Turbulent-image Restoration Based on a Compound Multibranch Feature Fusion Network

Banglian Xu,Yao Fang,Leihong Zhang,Dawei Zhang,Lulu Zheng Optical Society of Korea 2023 Current Optics and Photonics Vol.7 No.3

In middle- and long-distance imaging systems, due to the atmospheric turbulence caused by temperature, wind speed, humidity, and so on, light waves propagating in the air are distorted, resulting in image-quality degradation such as geometric deformation and fuzziness. In remote sensing, astronomical observation, and traffic monitoring, image information loss due to degradation causes huge losses, so effective restoration of degraded images is very important. To restore images degraded by atmospheric turbulence, an image-restoration method based on improved compound multibranch feature fusion (CMFNetPro) was proposed. Based on the CMFNet network, an efficient channel-attention mechanism was used to replace the channel-attention mechanism to improve image quality and network efficiency. In the experiment, two-dimensional random distortion vector fields were used to construct two turbulent datasets with different degrees of distortion, based on the Google Landmarks Dataset v2 dataset. The experimental results showed that compared to the CMFNet, DeblurGAN-v2, and MIMO-UNet models, the proposed CMFNetPro network achieves better performance in both quality and training cost of turbulent-image restoration. In the mixed training, CMFNetPro was 1.2391 dB (weak turbulence), 0.8602 dB (strong turbulence) respectively higher in terms of peak signal-to-noise ratio and 0.0015 (weak turbulence), 0.0136 (strong turbulence) respectively higher in terms of structure similarity compared to CMFNet. CMFNetPro was 14.4 hours faster compared to the CMFNet. This provides a feasible scheme for turbulent-image restoration based on deep learning.

Influence of Atmospheric Turbulence Channel on a Ghost-imaging Transmission System

Kaimin Wang,Zhaorui Wang,Leihong Zhang,Yi Kang,Hualong Ye,Jiafeng Hu,Jiaming Xu 한국광학회 2020 Current Optics and Photonics Vol.4 No.1

We research a system of compressed-sensing computational ghost imaging (CSCGI) based on the intensity fluctuation brought by turbulence. In this system, we used the gamma-gamma intensity-fluctuation model, which is commonly used in transmission systems, to simulate the CSCGI system. By setting proper values of the parameters such as transmission distance, refractive-index structure parameter, and sampling rates, the peak signal-to-noise ratio (PSNR) performance and bit-error rate (BER) performance are obtained to evaluate the imaging quality, which provides a theoretical model to further research the ghost-imaging algorithm.