This study proposes a novel particle encoding mechanism that seamlessly incorporates the quantum properties of particles,with a specific emphasis on constituent quarks.The primary objective of this mechanism is to fac...This study proposes a novel particle encoding mechanism that seamlessly incorporates the quantum properties of particles,with a specific emphasis on constituent quarks.The primary objective of this mechanism is to facilitate the digital registration and identification of a wide range of particle information.Its design ensures easy integration with different event generators and digital simulations commonly used in high-energy experiments.Moreover,this innovative framework can be easily expanded to encode complex multi-quark states comprising up to nine valence quarks and accommodating an angular momentum of up to 99/2.This versatility and scalability make it a valuable tool.展开更多
Leveraging the extraordinary phenomena of quantum superposition and quantum correlation,quantum computing offers unprecedented potential for addressing challenges beyond the reach of classical computers.This paper tac...Leveraging the extraordinary phenomena of quantum superposition and quantum correlation,quantum computing offers unprecedented potential for addressing challenges beyond the reach of classical computers.This paper tackles two pivotal challenges in the realm of quantum computing:firstly,the development of an effective encoding protocol for translating classical data into quantum states,a critical step for any quantum computation.Different encoding strategies can significantly influence quantum computer performance.Secondly,we address the need to counteract the inevitable noise that can hinder quantum acceleration.Our primary contribution is the introduction of a novel variational data encoding method,grounded in quantum regression algorithm models.By adapting the learning concept from machine learning,we render data encoding a learnable process.This allowed us to study the role of quantum correlation in data encoding.Through numerical simulations of various regression tasks,we demonstrate the efficacy of our variational data encoding,particularly post-learning from instructional data.Moreover,we delve into the role of quantum correlation in enhancing task performance,especially in noisy environments.Our findings underscore the critical role of quantum correlation in not only bolstering performance but also in mitigating noise interference,thus advancing the frontier of quantum computing.展开更多
The visual features of continuous pseudocolor encoding is discussed and the optimiz- ing design algorithm of continuous pseudocolor scale is derived.The algorithm is restricting the varying range and direction of ligh...The visual features of continuous pseudocolor encoding is discussed and the optimiz- ing design algorithm of continuous pseudocolor scale is derived.The algorithm is restricting the varying range and direction of lightness,hue and saturation according to correlation and naturalness,automatically calculating the chromaticity coordinates of nodes in uniform color space to get the longest length of scale path,then interpolating points between nodes in equal color differences to obtain continuous pseudocolor scale with visual uniformity.When it was applied to the pseudocolor encoding of thermal image displays,the results showed that the correlation and the naturalness of original images and cognitive characteristics of target pattern were reserved well;the dynamic range of visual perception and the amount of visual information increased obviously;the contrast sensitivity of target identification improved;and the blindness of scale design were avoided.展开更多
The translation activity is a process of the interlinguistic transmission of information realized by the information encoding and decoding.Encoding and decoding,cognitive practices operated in objective contexts,are i...The translation activity is a process of the interlinguistic transmission of information realized by the information encoding and decoding.Encoding and decoding,cognitive practices operated in objective contexts,are inevitably of selectivity ascribing to the restriction of contextual reasons.The translator as the intermediary agent connects the original author(encoder)and the target readers(decoder),shouldering the dual duties of the decoder and the encoder,for which his subjectivity is irrevocably manipulated by the selectivity of encoding and decoding.展开更多
Based on detailed analysis of advantages and disadvantages of the existing connected-component labeling （CCL） algorithm,a new algorithm for binary connected components labeling based on run-length encoding （RLE） a...Based on detailed analysis of advantages and disadvantages of the existing connected-component labeling （CCL） algorithm,a new algorithm for binary connected components labeling based on run-length encoding （RLE） and union-find sets has been put forward.The new algorithm uses RLE as the basic processing unit,converts the label merging of connected RLE into sets grouping in accordance with equivalence relation,and uses the union-find sets which is the realization method of sets grouping to solve the label merging of connected RLE.And the label merging procedure has been optimized：the union operation has been modified by adding the ＂weighted rule＂ to avoid getting a degenerated-tree,and the ＂path compression＂ has been adopted when implementing the find operation,then the time complexity of label merging is O（nα（n））.The experiments show that the new algorithm can label the connected components of any shapes very quickly and exactly,save more memory,and facilitate the subsequent image analysis.展开更多
Pilot plays an essential role in a duplex communication system.Several methods have been proposed for pilot assignment over specific scenarios.With the help of permutation encoding,we implemented a genetic algorithm f...Pilot plays an essential role in a duplex communication system.Several methods have been proposed for pilot assignment over specific scenarios.With the help of permutation encoding,we implemented a genetic algorithm for optimizing pilot assignment in a multi-user massive multiple input multiple output(MIMO)system.Results show improvement on existing results especially in the case of strong user estimation rates.展开更多
The non-binary(NB) Irregular Repeat Accumulate(IRA) codes, as a subclass of NB LDPC codes, potentially have an excellent error-correcting performance. They are also known to provide linear complexity of encoding, but ...The non-binary(NB) Irregular Repeat Accumulate(IRA) codes, as a subclass of NB LDPC codes, potentially have an excellent error-correcting performance. They are also known to provide linear complexity of encoding, but the basic encoding method with the serial rate-1 accumulator significantly limits the encoder throughput. Then the objective of the research presented in this paper is to develop an encoding method pro- viding significantly increased throughput of an NB-IRA encoder altogether with a flexible code construction methods for the structured(S-NB-IRA) codes eligible for the proposed encoding method. For this purpose, we reformulate the classic encoding algorithm to fit into the partial parallel encoder architecture. We propose the S-NB-IRA encoder block diagram and show that its estimated throughput is proportional to the submatrix size of the parity check matrix, which guarantees a wide complexity- throughput tradeoff. Then, in order to facilitate the S-NB-IRA coding systems design, we present a computer search algorithm for the construction of good S-NB-IRA codes. The algorithm aims at optimizing the code graph topology along with selecting an appropriate non-binary elements in the parity check matrix. Numerical results show that the constructed S-NB-IRA codes significantly outperform the binary IRA and S-IRA codes, while their performance is similar to the best unstructured NB-LDPC codes.展开更多
We design proposals to generate a remote Greenberger-Horne-Zeilinger（GHZ） state and a W state of nitrogenvacancy（NV） centers coupled to microtoroidal resonators（MTRs） through noisy channels by utilizing time-bin...We design proposals to generate a remote Greenberger-Horne-Zeilinger（GHZ） state and a W state of nitrogenvacancy（NV） centers coupled to microtoroidal resonators（MTRs） through noisy channels by utilizing time-bin encoding processes and fast-optical-switch-based polarization rotation operations.The polarization and phase noise induced by noisy channels generally affect the time of state generation but not its success probability and fidelity.Besides,the above proposals can be generalized to n-qubit between two or among n remote nodes with success probability unity under ideal conditions.Furthennore,the proposals are robust for regular noise-changeable channels for the n-node case.This method is also useful in other remote quantum information processing tasks through noisy channels.展开更多
Song [Song D 2004 Phys. Rev. A69034301] first proposed two key distribution schemes with the symmetry feature.We find that, in the schemes, the private channels which Alice and Bob publicly announce the initial Bell s...Song [Song D 2004 Phys. Rev. A69034301] first proposed two key distribution schemes with the symmetry feature.We find that, in the schemes, the private channels which Alice and Bob publicly announce the initial Bell state or the measurement result through are not needed in discovering keys, and Song’s encoding methods do not arrive at the optimization.Here, an optimized encoding method is given so that the efficiencies of Song’s schemes are improved by 7/3 times. Interestingly, this optimized encoding method can be extended to the key distribution scheme composed of generalized Bell states.展开更多
An effective Luby transform （LT） encoding algorithm based on short cycle elimination is proposed to improve decoding probabilities of short length LT codes. By searching the generator ma- trix, some special encoded ...An effective Luby transform （LT） encoding algorithm based on short cycle elimination is proposed to improve decoding probabilities of short length LT codes. By searching the generator ma- trix, some special encoded symbols are generated by the encoder to effectively break the short cycles that have negative effect on the performance of LT codes. Analysis and numerical results show that by employing the proposed algorithm, the encoding complexity decreases and the decoding probabili- ties improve both in binary erasure channels （BECs） and additive white gauss noise （AWGN） chan- nels.展开更多
Water exchange between the different compartments of a heterogeneous specimen can be characterized via diffusion magnetic resonance imaging(dMRI).Many analysis frameworks using dMRI data have been proposed to describe...Water exchange between the different compartments of a heterogeneous specimen can be characterized via diffusion magnetic resonance imaging(dMRI).Many analysis frameworks using dMRI data have been proposed to describe exchange,often using a double diffusion encoding(DDE)stimulated echo sequence.Techniques such as diffusion exchange weighted imaging(DEWI)and the filter exchange and rapid exchange models,use a specific subset of the full space DDE signal.In this work,a general representation of the DDE signal was employed with different sampling schemes(namely constant b1,diagonal and anti-diagonal)from the data reduction models to estimate exchange.A near-uniform sampling scheme was proposed and compared with the other sampling schemes.The filter exchange and rapid exchange models were also applied to estimate exchange with their own subsampling schemes.These subsampling schemes and models were compared on both simulated data and experimental data acquired with a benchtop MR scanner.In synthetic data,the diagonal and near-uniform sampling schemes performed the best due to the consistency of their estimates with the ground truth.In experimental data,the shifted diagonal and near-uniform sampling schemes outperformed the others,yielding the most consistent estimates with the full space estimation.The results suggest the feasibility of measuring exchange using a general representation of the DDE signal along with variable sampling schemes.In future studies,algorithms could be further developed for the optimization of sampling schemes,as well as incorporating additional properties,such as geometry and diffusion anisotropy,into exchange frameworks.展开更多
Images and videos provide a wealth of information for people in production and life.Although most digital information is transmitted via optical fiber,the image acquisition and transmission processes still rely heavil...Images and videos provide a wealth of information for people in production and life.Although most digital information is transmitted via optical fiber,the image acquisition and transmission processes still rely heavily on electronic circuits.The development of all-optical transmission networks and optical computing frameworks has pointed to the direction for the next generation of data transmission and information processing.Here,we propose a high-speed,low-cost,multiplexed parallel and one-piece all-fiber architecture for image acquisition,encoding,and transmission,called the Multicore Fiber Acquisition and Transmission Image System(MFAT).Based on different spatial and modal channels of the multicore fiber,fiber-coupled self-encoding,and digital aperture decoding technology,scenes can be observed directly from up to 1 km away.The expansion of capacity provides the possibility of parallel coded transmission of multimodal high-quality data.MFAT requires no additional signal transmitting and receiving equipment.The all-fiber processing saves the time traditionally spent on signal conversion and image pre-processing(compression,encoding,and modulation).Additionally,it provides an effective solution for 2D information acquisition and transmission tasks in extreme environments such as high temperatures and electromagnetic interference.展开更多
An approach for color image segmentation is proposed based on the contributions of color features to segmentation rather than the choice of a particular color space. The determination of effective color features depen...An approach for color image segmentation is proposed based on the contributions of color features to segmentation rather than the choice of a particular color space. The determination of effective color features depends on the analysis of various color features from each tested color image via the designed feature encoding. It is different from the pervious methods where self organized feature map (SOFM) is used for constructing the feature encoding so that the feature encoding can self organize the effective features for different color images. Fuzzy clustering is applied for the final segmentation when the well suited color features and the initial parameter are available. The proposed method has been applied in segmenting different types of color images and the experimental results show that it outperforms the classical clustering method. The study shows that the feature encoding approach offers great promise in automating and optimizing the segmentation of color images.展开更多
流媒体技术是当前网络应用的主流技术之一,编码器是流媒体系统的重要组成部分.本文以微软公司提供的流媒体编码器Windows Media Encoder为例,通过剖析用于该编码器二次开发的SDK英文文档,归纳了利用该SDK对流媒体编码器进行二次开发的...流媒体技术是当前网络应用的主流技术之一,编码器是流媒体系统的重要组成部分.本文以微软公司提供的流媒体编码器Windows Media Encoder为例,通过剖析用于该编码器二次开发的SDK英文文档,归纳了利用该SDK对流媒体编码器进行二次开发的基本步骤,并以实例说明实际的编程思路.展开更多
Metasurface provides subwavelength structures for manipulating wavefronts of light. The benefits of subwavelength components offer a continuous modulation of amplitude, phase, and polarization, thus eliminating the pr...Metasurface provides subwavelength structures for manipulating wavefronts of light. The benefits of subwavelength components offer a continuous modulation of amplitude, phase, and polarization, thus eliminating the production of higher-order images and improving the utilization of light intensity. Despite the rapid progress in this field, multiparameter control of light using single layer metasurface is rarely reported. In fact, multiparameter control of light helps to improve information storage capacity and image fidelity. With simultaneous manipulation of polarization and amplitude at each pixel, it is possible to encode two separate images into one metasurface and reconstruct them under proper conditions. In a proof of concept experiment, we demonstrate an independent display of two binary images at the same position with polarization de-multiplexing from a single metasurface. This unique technology of encoding two images through amplitude and polarization manipulation provides a new opportunity for various applications in, such as encryption, information storage, polarization holograms, optical communications and fundamental physics.展开更多
Optical cryptanalysis is essential to the further investigation of more secure optical cryptosystems.Learning-based at-tack of optical encryption eliminates the need for the retrieval of random phase keys of optical e...Optical cryptanalysis is essential to the further investigation of more secure optical cryptosystems.Learning-based at-tack of optical encryption eliminates the need for the retrieval of random phase keys of optical encryption systems but it is limited for practical applications since it requires a large set of plaintext-ciphertext pairs for the cryptosystem to be at-tacked.Here,we propose a two-step deep learning strategy for ciphertext-only attack(COA)on the classical double ran-dom phase encryption(DRPE).Specifically,we construct a virtual DRPE system to gather the training data.Besides,we divide the inverse problem in COA into two more specific inverse problems and employ two deep neural networks(DNNs)to respectively learn the removal of speckle noise in the autocorrelation domain and the de-correlation operation to retrieve the plaintext image.With these two trained DNNs at hand,we show that the plaintext can be predicted in real-time from an unknown ciphertext alone.The proposed learning-based COA method dispenses with not only the retrieval of random phase keys but also the invasive data acquisition of plaintext-ciphertext pairs in the DPRE system.Numerical simulations and optical experiments demonstrate the feasibility and effectiveness of the proposed learning-based COA method.展开更多
基金the Department of Education of Hunan Province,China(No.21A0541)the U.S.Department of Energy(No.DE-FG03-93ER40773)H.Z.acknowledges the financial support from Key Laboratory of Quark and Lepton Physics in Central China Normal University(No.QLPL2024P01)。
文摘This study proposes a novel particle encoding mechanism that seamlessly incorporates the quantum properties of particles,with a specific emphasis on constituent quarks.The primary objective of this mechanism is to facilitate the digital registration and identification of a wide range of particle information.Its design ensures easy integration with different event generators and digital simulations commonly used in high-energy experiments.Moreover,this innovative framework can be easily expanded to encode complex multi-quark states comprising up to nine valence quarks and accommodating an angular momentum of up to 99/2.This versatility and scalability make it a valuable tool.
基金the National Natural Science Foun-dation of China(Grant Nos.12105090 and 12175057).
文摘Leveraging the extraordinary phenomena of quantum superposition and quantum correlation,quantum computing offers unprecedented potential for addressing challenges beyond the reach of classical computers.This paper tackles two pivotal challenges in the realm of quantum computing:firstly,the development of an effective encoding protocol for translating classical data into quantum states,a critical step for any quantum computation.Different encoding strategies can significantly influence quantum computer performance.Secondly,we address the need to counteract the inevitable noise that can hinder quantum acceleration.Our primary contribution is the introduction of a novel variational data encoding method,grounded in quantum regression algorithm models.By adapting the learning concept from machine learning,we render data encoding a learnable process.This allowed us to study the role of quantum correlation in data encoding.Through numerical simulations of various regression tasks,we demonstrate the efficacy of our variational data encoding,particularly post-learning from instructional data.Moreover,we delve into the role of quantum correlation in enhancing task performance,especially in noisy environments.Our findings underscore the critical role of quantum correlation in not only bolstering performance but also in mitigating noise interference,thus advancing the frontier of quantum computing.
文摘The visual features of continuous pseudocolor encoding is discussed and the optimiz- ing design algorithm of continuous pseudocolor scale is derived.The algorithm is restricting the varying range and direction of lightness,hue and saturation according to correlation and naturalness,automatically calculating the chromaticity coordinates of nodes in uniform color space to get the longest length of scale path,then interpolating points between nodes in equal color differences to obtain continuous pseudocolor scale with visual uniformity.When it was applied to the pseudocolor encoding of thermal image displays,the results showed that the correlation and the naturalness of original images and cognitive characteristics of target pattern were reserved well;the dynamic range of visual perception and the amount of visual information increased obviously;the contrast sensitivity of target identification improved;and the blindness of scale design were avoided.
文摘The translation activity is a process of the interlinguistic transmission of information realized by the information encoding and decoding.Encoding and decoding,cognitive practices operated in objective contexts,are inevitably of selectivity ascribing to the restriction of contextual reasons.The translator as the intermediary agent connects the original author(encoder)and the target readers(decoder),shouldering the dual duties of the decoder and the encoder,for which his subjectivity is irrevocably manipulated by the selectivity of encoding and decoding.
文摘Based on detailed analysis of advantages and disadvantages of the existing connected-component labeling （CCL） algorithm,a new algorithm for binary connected components labeling based on run-length encoding （RLE） and union-find sets has been put forward.The new algorithm uses RLE as the basic processing unit,converts the label merging of connected RLE into sets grouping in accordance with equivalence relation,and uses the union-find sets which is the realization method of sets grouping to solve the label merging of connected RLE.And the label merging procedure has been optimized：the union operation has been modified by adding the ＂weighted rule＂ to avoid getting a degenerated-tree,and the ＂path compression＂ has been adopted when implementing the find operation,then the time complexity of label merging is O（nα（n））.The experiments show that the new algorithm can label the connected components of any shapes very quickly and exactly,save more memory,and facilitate the subsequent image analysis.
文摘Pilot plays an essential role in a duplex communication system.Several methods have been proposed for pilot assignment over specific scenarios.With the help of permutation encoding,we implemented a genetic algorithm for optimizing pilot assignment in a multi-user massive multiple input multiple output(MIMO)system.Results show improvement on existing results especially in the case of strong user estimation rates.
基金supported by the Polish Ministry of Science and Higher Education funding for statutory activities (decision no. 8686/E-367/S/2015 of 19 February 2015)
文摘The non-binary(NB) Irregular Repeat Accumulate(IRA) codes, as a subclass of NB LDPC codes, potentially have an excellent error-correcting performance. They are also known to provide linear complexity of encoding, but the basic encoding method with the serial rate-1 accumulator significantly limits the encoder throughput. Then the objective of the research presented in this paper is to develop an encoding method pro- viding significantly increased throughput of an NB-IRA encoder altogether with a flexible code construction methods for the structured(S-NB-IRA) codes eligible for the proposed encoding method. For this purpose, we reformulate the classic encoding algorithm to fit into the partial parallel encoder architecture. We propose the S-NB-IRA encoder block diagram and show that its estimated throughput is proportional to the submatrix size of the parity check matrix, which guarantees a wide complexity- throughput tradeoff. Then, in order to facilitate the S-NB-IRA coding systems design, we present a computer search algorithm for the construction of good S-NB-IRA codes. The algorithm aims at optimizing the code graph topology along with selecting an appropriate non-binary elements in the parity check matrix. Numerical results show that the constructed S-NB-IRA codes significantly outperform the binary IRA and S-IRA codes, while their performance is similar to the best unstructured NB-LDPC codes.
基金supported by the National Natural Science Foundation of China(Grant Nos.11264042,61465013,11465020,and 11165015)the Program for Chun Miao Excellent Talents of Jilin Provincial Department of Education(Grant No.201316)the Talent Program of Yanbian University of China(Grant No.950010001)
文摘We design proposals to generate a remote Greenberger-Horne-Zeilinger（GHZ） state and a W state of nitrogenvacancy（NV） centers coupled to microtoroidal resonators（MTRs） through noisy channels by utilizing time-bin encoding processes and fast-optical-switch-based polarization rotation operations.The polarization and phase noise induced by noisy channels generally affect the time of state generation but not its success probability and fidelity.Besides,the above proposals can be generalized to n-qubit between two or among n remote nodes with success probability unity under ideal conditions.Furthennore,the proposals are robust for regular noise-changeable channels for the n-node case.This method is also useful in other remote quantum information processing tasks through noisy channels.
基金supported by the National Natural Science Foundation of China(Grant No.11205115)the Program for Academic Leader Reserve Candidates in Tongling University(Grant No.2014tlxyxs30)the 2014-year Program for Excellent Youth Talents in University of Anhui Province,China
文摘Song [Song D 2004 Phys. Rev. A69034301] first proposed two key distribution schemes with the symmetry feature.We find that, in the schemes, the private channels which Alice and Bob publicly announce the initial Bell state or the measurement result through are not needed in discovering keys, and Song’s encoding methods do not arrive at the optimization.Here, an optimized encoding method is given so that the efficiencies of Song’s schemes are improved by 7/3 times. Interestingly, this optimized encoding method can be extended to the key distribution scheme composed of generalized Bell states.
基金Supported by China Mobile Research Institute and China National S&T Major Project(2010ZX03003-003)
文摘An effective Luby transform （LT） encoding algorithm based on short cycle elimination is proposed to improve decoding probabilities of short length LT codes. By searching the generator ma- trix, some special encoded symbols are generated by the encoder to effectively break the short cycles that have negative effect on the performance of LT codes. Analysis and numerical results show that by employing the proposed algorithm, the encoding complexity decreases and the decoding probabili- ties improve both in binary erasure channels （BECs） and additive white gauss noise （AWGN） chan- nels.
基金the Swedish Foundation for International Cooperation in Research and Higher Education(STINT),and the Swedish Research Council(Dnr 2022e04715).
文摘Water exchange between the different compartments of a heterogeneous specimen can be characterized via diffusion magnetic resonance imaging(dMRI).Many analysis frameworks using dMRI data have been proposed to describe exchange,often using a double diffusion encoding(DDE)stimulated echo sequence.Techniques such as diffusion exchange weighted imaging(DEWI)and the filter exchange and rapid exchange models,use a specific subset of the full space DDE signal.In this work,a general representation of the DDE signal was employed with different sampling schemes(namely constant b1,diagonal and anti-diagonal)from the data reduction models to estimate exchange.A near-uniform sampling scheme was proposed and compared with the other sampling schemes.The filter exchange and rapid exchange models were also applied to estimate exchange with their own subsampling schemes.These subsampling schemes and models were compared on both simulated data and experimental data acquired with a benchtop MR scanner.In synthetic data,the diagonal and near-uniform sampling schemes performed the best due to the consistency of their estimates with the ground truth.In experimental data,the shifted diagonal and near-uniform sampling schemes outperformed the others,yielding the most consistent estimates with the full space estimation.The results suggest the feasibility of measuring exchange using a general representation of the DDE signal along with variable sampling schemes.In future studies,algorithms could be further developed for the optimization of sampling schemes,as well as incorporating additional properties,such as geometry and diffusion anisotropy,into exchange frameworks.
基金financial supports from the National Key R&D Program of China (2021YFA1401103)the National Natural Science Foundation of China (61925502 and 51772145)
文摘Images and videos provide a wealth of information for people in production and life.Although most digital information is transmitted via optical fiber,the image acquisition and transmission processes still rely heavily on electronic circuits.The development of all-optical transmission networks and optical computing frameworks has pointed to the direction for the next generation of data transmission and information processing.Here,we propose a high-speed,low-cost,multiplexed parallel and one-piece all-fiber architecture for image acquisition,encoding,and transmission,called the Multicore Fiber Acquisition and Transmission Image System(MFAT).Based on different spatial and modal channels of the multicore fiber,fiber-coupled self-encoding,and digital aperture decoding technology,scenes can be observed directly from up to 1 km away.The expansion of capacity provides the possibility of parallel coded transmission of multimodal high-quality data.MFAT requires no additional signal transmitting and receiving equipment.The all-fiber processing saves the time traditionally spent on signal conversion and image pre-processing(compression,encoding,and modulation).Additionally,it provides an effective solution for 2D information acquisition and transmission tasks in extreme environments such as high temperatures and electromagnetic interference.
文摘An approach for color image segmentation is proposed based on the contributions of color features to segmentation rather than the choice of a particular color space. The determination of effective color features depends on the analysis of various color features from each tested color image via the designed feature encoding. It is different from the pervious methods where self organized feature map (SOFM) is used for constructing the feature encoding so that the feature encoding can self organize the effective features for different color images. Fuzzy clustering is applied for the final segmentation when the well suited color features and the initial parameter are available. The proposed method has been applied in segmenting different types of color images and the experimental results show that it outperforms the classical clustering method. The study shows that the feature encoding approach offers great promise in automating and optimizing the segmentation of color images.
基金the 973 Program of China (grant No. 2013CBA01702)the National Natural Science Foundation of China (grant Nos. 11474206, 11404224, 1174243, and 11774246)+4 种基金the Beijing Youth Top-Notch Talent Training Plan (CIT&TCD 201504080)the Beijing Nova Program (grant No. Z161100004916100)the Beijing Talents Project (grant No. 2018A19)Capacity Building for Science & Technology Innovation-Fundamental Scientific Research Funds (grand No. 025185305000/142)the Scientific Research Base Development Program of the Beijing Municipal Commission of Education.
文摘Metasurface provides subwavelength structures for manipulating wavefronts of light. The benefits of subwavelength components offer a continuous modulation of amplitude, phase, and polarization, thus eliminating the production of higher-order images and improving the utilization of light intensity. Despite the rapid progress in this field, multiparameter control of light using single layer metasurface is rarely reported. In fact, multiparameter control of light helps to improve information storage capacity and image fidelity. With simultaneous manipulation of polarization and amplitude at each pixel, it is possible to encode two separate images into one metasurface and reconstruct them under proper conditions. In a proof of concept experiment, we demonstrate an independent display of two binary images at the same position with polarization de-multiplexing from a single metasurface. This unique technology of encoding two images through amplitude and polarization manipulation provides a new opportunity for various applications in, such as encryption, information storage, polarization holograms, optical communications and fundamental physics.
基金financial supports from the National Natural Science Foundation of China(NSFC)(62061136005,61705141,61805152,61875129,61701321)Sino-German Research Collaboration Group(GZ 1391)+2 种基金the Mobility program(M-0044)sponsored by the Sino-German CenterChinese Academy of Sciences(QYZDB-SSW-JSC002)Science and Technology Innovation Commission of Shenzhen(JCYJ20170817095047279)。
文摘Optical cryptanalysis is essential to the further investigation of more secure optical cryptosystems.Learning-based at-tack of optical encryption eliminates the need for the retrieval of random phase keys of optical encryption systems but it is limited for practical applications since it requires a large set of plaintext-ciphertext pairs for the cryptosystem to be at-tacked.Here,we propose a two-step deep learning strategy for ciphertext-only attack(COA)on the classical double ran-dom phase encryption(DRPE).Specifically,we construct a virtual DRPE system to gather the training data.Besides,we divide the inverse problem in COA into two more specific inverse problems and employ two deep neural networks(DNNs)to respectively learn the removal of speckle noise in the autocorrelation domain and the de-correlation operation to retrieve the plaintext image.With these two trained DNNs at hand,we show that the plaintext can be predicted in real-time from an unknown ciphertext alone.The proposed learning-based COA method dispenses with not only the retrieval of random phase keys but also the invasive data acquisition of plaintext-ciphertext pairs in the DPRE system.Numerical simulations and optical experiments demonstrate the feasibility and effectiveness of the proposed learning-based COA method.
