In recent years,deep learning has been introduced into the field of Single-pixel imaging(SPI),garnering significant attention.However,conventional networks still exhibit limitations in preserving image details.To addr...In recent years,deep learning has been introduced into the field of Single-pixel imaging(SPI),garnering significant attention.However,conventional networks still exhibit limitations in preserving image details.To address this issue,we integrate Large Kernel Convolution(LKconv)into the U-Net framework,proposing an enhanced network structure named U-LKconv network,which significantly enhances the capability to recover image details even under low sampling conditions.展开更多
In the field of imaging,the image resolution is required to be higher.There is always a contradiction between the sensitivity and resolution of the seeker in the infrared guidance system.This work uses the rosette sca...In the field of imaging,the image resolution is required to be higher.There is always a contradiction between the sensitivity and resolution of the seeker in the infrared guidance system.This work uses the rosette scanning mode for physical compression imaging in order to improve the resolution of the image as much as possible under the high-sensitivity infrared rosette point scanning mode and complete the missing information that is not scanned.It is effective to use optical lens instead of traditional optical reflection system,which can reduce the loss in optical path transmission.At the same time,deep learning neural network is used for control.An infrared single pixel imaging system that integrates sparse algorithm and recovery algorithm through the improved generative adversarial networks is trained.The experiment on the infrared aerial target dataset shows that when the input is sparse image after rose sampling,the system finally can realize the single pixel recovery imaging of the infrared image,which improves the resolution of the image while ensuring high sensitivity.展开更多
Single pixel imaging is a novel imaging technique,and it becomes a focus of research in recent years due to its advantages such as high lateral resolution and high robustness to noise.Imaging speed is one of the criti...Single pixel imaging is a novel imaging technique,and it becomes a focus of research in recent years due to its advantages such as high lateral resolution and high robustness to noise.Imaging speed is one of the critical shortcomings,which limits the further development and applications of this technique.In this paper,we focus on the issues of imaging efficiency of a single pixel imaging system.We propose semi-continuous wavelet transform(SCWT)protocol and introduce the protocol into the single pixel imaging system.The proposed protocol is something between continuous wavelet transform and discrete wavelet transform,which allows the usage of those smooth(usually non-orthogonal,and they have advantages in representing smooth signals compressively,which can improve the imaging speed of single pixel imaging)wavelets and with limited numbers of measurements.The proposed imaging scheme is studied,and verified by simulations and experiments.Furthermore,a comparison between our proposed scheme and existing imaging schemes are given.According to the results,the proposed SCWT scheme is proved to be effective in reconstructing a image compressively.展开更多
In single-pixel imaging or computational ghost imaging,the measurement matrix has a great impact on the performance of the imaging system,because it involves modulation of the optical signal and image reconstruction.T...In single-pixel imaging or computational ghost imaging,the measurement matrix has a great impact on the performance of the imaging system,because it involves modulation of the optical signal and image reconstruction.The measurement matrix reported in the existing literatures is first binarized and then loaded onto the digital micro-mirror device(DMD)for optical modulation,that is,each pixel can only be modulated into on-off states.In this paper,we propose a digital grayscale modulation method for more efficient compressive sampling.On the basis of this,we demonstrate a single photon compressive imaging system.A control and counting circuit,based on field-programmable gate array(FPGA),is developed to control DMD to conduct digital grayscale modulation and count single-photon pulse output from the photomultiplier tube(PMT)simultaneously.The experimental results show that the imaging reconstruction quality can be improved by increasing the sparsity ratio properly and compressive sampling ratio(SR)of these gray-scale matrices.However,when the compressive SR and sparsity ratio are increased appropriately to a certain value,the reconstruction quality is usually saturated,and the imaging reconstruction quality of the digital grayscale modulation is better than that of binary modulation.展开更多
Driven by the necessity to strengthen information security during data collection and storage,the strategic convergence of computational imaging techniques is swiftly emerging as a dominant trend in the field of optic...Driven by the necessity to strengthen information security during data collection and storage,the strategic convergence of computational imaging techniques is swiftly emerging as a dominant trend in the field of optical encryption for data protection.This paper presents a two-layer security framework that combines full-color singlepixel imaging(SPI)with a micron-hole array.The micron-hole array is generated using a deep-learning algorithm and fabricated through lithography.The full-color Fourier SPI system,equipped with a single bucket detector,efficiently collects and encrypts image information.The illumination pattern sequence for SPI,derived from the optical diffraction image of the micron-hole array,imparts inherent physical security to the system.This study meticulously incorporates holographic encryption using a micron-hole array in the entire SPI encoding-decoding process,thus exploiting the complexity of algorithms and the physical non-clonability of components.Both numerical simulations and optical experiments confirm the stability of the framework in terms of encryption and security performance.This paves the way for new perspectives in anti-counterfeiting applications grounded in computational imaging and multi-dimensional optical cryptography,offering potential for practical advancements in the field.展开更多
Single-pixel imaging(SPI)through complex media remains challenging.In this paper,we report high-resolution common-path SPI with dual polarization using random-frequency-encoded time sequences in complex environments w...Single-pixel imaging(SPI)through complex media remains challenging.In this paper,we report high-resolution common-path SPI with dual polarization using random-frequency-encoded time sequences in complex environments where the illumination and detection paths are severely distorted.By leveraging a common-path optical configuration with orthogonal polarization states,a series of dynamic scaling factors can be corrected.The designed random-frequency encoding scheme disperses scattering-induced noise into artifacts to be simply removed.It is demonstrated in optical experiments that the proposed method is feasible and effective to reconstruct highresolution object images in complex environments.The proposed method does not require complex optical components and prior knowledge about scattering media,providing a robust solution for high-resolution optical imaging in complex scenarios where the illumination and detection paths are severely distorted at the same time.展开更多
Single-pixel imaging(SPI)faces significant challenges in reconstructing high-quality images under complex real-world degradation conditions.This paper presents an innovative degradation model for the physical processe...Single-pixel imaging(SPI)faces significant challenges in reconstructing high-quality images under complex real-world degradation conditions.This paper presents an innovative degradation model for the physical processes in SPI,providing the first comprehensive and quantitative analysis of various SPI noise sources encountered in real-world applications.Especially,pattern-dependent global noise propagation and object jitter modelling methods for SPI are proposed.Subsequently,a deep-blind neural network is developed to remove the necessity of obtaining parameters of all the degradation factors in real-world image compensation.Our method can operate without degradation parameters and significantly improve the resolution and fidelity of SPI image reconstruction.The deep-blind network training is guided by the proposed comprehensive SPI degradation model that describes real-world SPI impairments,enabling the network to generalize across a wide range of degradation combinations.The experiment validates its advanced performance in real-world SPI imaging at ultra-low sampling rates.The proposed method holds great potential for applications in remote sensing,biomedical imaging,and privacy-preserving surveillance.展开更多
文摘In recent years,deep learning has been introduced into the field of Single-pixel imaging(SPI),garnering significant attention.However,conventional networks still exhibit limitations in preserving image details.To address this issue,we integrate Large Kernel Convolution(LKconv)into the U-Net framework,proposing an enhanced network structure named U-LKconv network,which significantly enhances the capability to recover image details even under low sampling conditions.
基金the Fundamental Research Funds for the Central Universities(No.3072022CF0802)。
文摘In the field of imaging,the image resolution is required to be higher.There is always a contradiction between the sensitivity and resolution of the seeker in the infrared guidance system.This work uses the rosette scanning mode for physical compression imaging in order to improve the resolution of the image as much as possible under the high-sensitivity infrared rosette point scanning mode and complete the missing information that is not scanned.It is effective to use optical lens instead of traditional optical reflection system,which can reduce the loss in optical path transmission.At the same time,deep learning neural network is used for control.An infrared single pixel imaging system that integrates sparse algorithm and recovery algorithm through the improved generative adversarial networks is trained.The experiment on the infrared aerial target dataset shows that when the input is sparse image after rose sampling,the system finally can realize the single pixel recovery imaging of the infrared image,which improves the resolution of the image while ensuring high sensitivity.
基金the Natural Science Foundation of Jilin Province,China(Grand No.YDZJ202101ZYTS030)。
文摘Single pixel imaging is a novel imaging technique,and it becomes a focus of research in recent years due to its advantages such as high lateral resolution and high robustness to noise.Imaging speed is one of the critical shortcomings,which limits the further development and applications of this technique.In this paper,we focus on the issues of imaging efficiency of a single pixel imaging system.We propose semi-continuous wavelet transform(SCWT)protocol and introduce the protocol into the single pixel imaging system.The proposed protocol is something between continuous wavelet transform and discrete wavelet transform,which allows the usage of those smooth(usually non-orthogonal,and they have advantages in representing smooth signals compressively,which can improve the imaging speed of single pixel imaging)wavelets and with limited numbers of measurements.The proposed imaging scheme is studied,and verified by simulations and experiments.Furthermore,a comparison between our proposed scheme and existing imaging schemes are given.According to the results,the proposed SCWT scheme is proved to be effective in reconstructing a image compressively.
基金This work was supported in part by the National Natural Science Foundation of China(Grants Nos.61865010 and 61565012)in part by the China Postdoctoral Science Foundation(Grant No.2015T80691)+1 种基金in part by the Science and Technology Plan Project of Jiangxi Province(Grant No.20151BBE50092)in part by the Funding Scheme to Outstanding Young Talents of Jiangxi Province(Grant No.20171BCB23007).
文摘In single-pixel imaging or computational ghost imaging,the measurement matrix has a great impact on the performance of the imaging system,because it involves modulation of the optical signal and image reconstruction.The measurement matrix reported in the existing literatures is first binarized and then loaded onto the digital micro-mirror device(DMD)for optical modulation,that is,each pixel can only be modulated into on-off states.In this paper,we propose a digital grayscale modulation method for more efficient compressive sampling.On the basis of this,we demonstrate a single photon compressive imaging system.A control and counting circuit,based on field-programmable gate array(FPGA),is developed to control DMD to conduct digital grayscale modulation and count single-photon pulse output from the photomultiplier tube(PMT)simultaneously.The experimental results show that the imaging reconstruction quality can be improved by increasing the sparsity ratio properly and compressive sampling ratio(SR)of these gray-scale matrices.However,when the compressive SR and sparsity ratio are increased appropriately to a certain value,the reconstruction quality is usually saturated,and the imaging reconstruction quality of the digital grayscale modulation is better than that of binary modulation.
基金National Natural Science Foundation of China(62375245,61975185,61575178).
文摘Driven by the necessity to strengthen information security during data collection and storage,the strategic convergence of computational imaging techniques is swiftly emerging as a dominant trend in the field of optical encryption for data protection.This paper presents a two-layer security framework that combines full-color singlepixel imaging(SPI)with a micron-hole array.The micron-hole array is generated using a deep-learning algorithm and fabricated through lithography.The full-color Fourier SPI system,equipped with a single bucket detector,efficiently collects and encrypts image information.The illumination pattern sequence for SPI,derived from the optical diffraction image of the micron-hole array,imparts inherent physical security to the system.This study meticulously incorporates holographic encryption using a micron-hole array in the entire SPI encoding-decoding process,thus exploiting the complexity of algorithms and the physical non-clonability of components.Both numerical simulations and optical experiments confirm the stability of the framework in terms of encryption and security performance.This paves the way for new perspectives in anti-counterfeiting applications grounded in computational imaging and multi-dimensional optical cryptography,offering potential for practical advancements in the field.
基金National Natural Science Foundation of China(62405256)Hong Kong Research Grants Council General Research Fund(15224921,15223522,15237924)+2 种基金Hong Kong Research Grants Council Collaborative Research Fund(C5047-24G)Basic and Applied Basic Research Foundation of Guangdong Province(2023A1515010831,2025A1515011411)The Hong Kong Polytechnic University(1-CDJA,1-WZ4M).
文摘Single-pixel imaging(SPI)through complex media remains challenging.In this paper,we report high-resolution common-path SPI with dual polarization using random-frequency-encoded time sequences in complex environments where the illumination and detection paths are severely distorted.By leveraging a common-path optical configuration with orthogonal polarization states,a series of dynamic scaling factors can be corrected.The designed random-frequency encoding scheme disperses scattering-induced noise into artifacts to be simply removed.It is demonstrated in optical experiments that the proposed method is feasible and effective to reconstruct highresolution object images in complex environments.The proposed method does not require complex optical components and prior knowledge about scattering media,providing a robust solution for high-resolution optical imaging in complex scenarios where the illumination and detection paths are severely distorted at the same time.
基金National Natural Science Foundation of China(62305184)Science,Technology and Innovation Commission of Shenzhen Municipality(JCYJ20241202123919027)+1 种基金Science,Technology and Innovation Commission of Shenzhen Municipality(WDZC20220818100259004)Basic and Applied Basic Research Foundation of Guangdong Province(2023A1515012932).
文摘Single-pixel imaging(SPI)faces significant challenges in reconstructing high-quality images under complex real-world degradation conditions.This paper presents an innovative degradation model for the physical processes in SPI,providing the first comprehensive and quantitative analysis of various SPI noise sources encountered in real-world applications.Especially,pattern-dependent global noise propagation and object jitter modelling methods for SPI are proposed.Subsequently,a deep-blind neural network is developed to remove the necessity of obtaining parameters of all the degradation factors in real-world image compensation.Our method can operate without degradation parameters and significantly improve the resolution and fidelity of SPI image reconstruction.The deep-blind network training is guided by the proposed comprehensive SPI degradation model that describes real-world SPI impairments,enabling the network to generalize across a wide range of degradation combinations.The experiment validates its advanced performance in real-world SPI imaging at ultra-low sampling rates.The proposed method holds great potential for applications in remote sensing,biomedical imaging,and privacy-preserving surveillance.
