Crime scene investigation(CSI)image is key evidence carrier during criminal investiga-tion,in which CSI image retrieval can assist the public police to obtain criminal clues.Moreover,with the rapid development of deep...Crime scene investigation(CSI)image is key evidence carrier during criminal investiga-tion,in which CSI image retrieval can assist the public police to obtain criminal clues.Moreover,with the rapid development of deep learning,data-driven paradigm has become the mainstreammethod of CSI image feature extraction and representation,and in this process,datasets provideeffective support for CSI retrieval performance.However,there is a lack of systematic research onCSI image retrieval methods and datasets.Therefore,we present an overview of the existing worksabout one-class and multi-class CSI image retrieval based on deep learning.According to theresearch,based on their technical functionalities and implementation methods,CSI image retrievalis roughly classified into five categories:feature representation,metric learning,generative adversar-ial networks,autoencoder networks and attention networks.Furthermore,We analyzed the remain-ing challenges and discussed future work directions in this field.展开更多
According to the conclusion of the simulation experiments in paper I, the Tikhonov regularization method is applied to cyclone wind retrieval with a rain-effect-considering geophysical model function （called CMF＋Rai...According to the conclusion of the simulation experiments in paper I, the Tikhonov regularization method is applied to cyclone wind retrieval with a rain-effect-considering geophysical model function （called CMF＋Rain）. The CMF＋Rain model which is based on the NASA scatterometer-2 （NSCAT2） GMF is presented to compensate for the effects of rain on cyclone wind retrieval. With the multiple solution scheme （MSS）, the noise of wind retrieval is effectively suppressed, but the influence of the background increases. It will cause a large wind direction error in ambiguity removal when the background error is large. However, this can be mitigated by the new ambiguity removal method of Tikhonov regularization as proved in the simulation experiments. A case study on an extratropical cyclone of hurricane observed with SeaWinds at 25-km resolution shows that the retrieved wind speed for areas with rain is in better agreement with that derived from the best track analysis for the GMF＋Rain model, but the wind direction obtained with the two-dimensional variational （2DVAR） ambiguity removal is incorrect. The new method of Tikhonov regularization effectively improves the performance of wind direction ambiguity removal through choosing appropriate regularization parameters and the retrieved wind speed is almost the same as that obtained from the 2DVAR.展开更多
In order to improve the utilization ratio of knowledge retrieval, a product-design knowledge retrieval approach based on ontology is proposed. A representation model of product-design knowledge is proposed according t...In order to improve the utilization ratio of knowledge retrieval, a product-design knowledge retrieval approach based on ontology is proposed. A representation model of product-design knowledge is proposed according to its characteristics. Domain ontology of product-design is estab- lished and the semantic annotation technology is used to connect the design knowledge and ontolo- gy. A new semantic annotation format is developed and semantic information of the design knowl- edge is enriched by making use of ontology. On that basis a retrieval algorithm is designed for semantic retrieval. Finally, this approach is used in a knowledge management system for military-vehi- cle design and its effectiveness and feasibility are validated. Results show that the recall ratio and the precision ratio of knowledge retrieval are improved greatly and users＇ requirements in semantic retrieval are satisfied.展开更多
A hybrid model that is based on the Combination of keywords and concept was put forward. The hybrid model is built on vector space model and probabilistic reasoning network. It not only can exert the advantages of key...A hybrid model that is based on the Combination of keywords and concept was put forward. The hybrid model is built on vector space model and probabilistic reasoning network. It not only can exert the advantages of keywords retrieval and concept retrieval but also can compensate for their shortcomings. Their parameters can be adjusted according to different usage in order to accept the best information retrieval result, and it has been proved by our experiments.展开更多
Shelterbelts are important in defending against natural disaster and maintaining ecological balances in farmland. Understanding of the shelterbelt vegetation fraction is fundamental to regional research of shelterbelt...Shelterbelts are important in defending against natural disaster and maintaining ecological balances in farmland. Understanding of the shelterbelt vegetation fraction is fundamental to regional research of shelterbelts using remote sensing. We used SPOT5 imagery with 10×10m spatial resolution in combination with knowledge of the characteristics of shelterbelts to develop a method for retrieval of the vegetation fraction of shelterbelts by the pixel un-mixing model. We then used the method to retrieve values for shelterbelts in study area. By combining the parameters of photographic images with characteristics of shelterbelts, we developed a method for measuring the vegetation fraction of shelterbelts based on an advanced photographic method. We then measured the actual values to validate the retrieval result. The multiple correlation coefficients between the retrieved and measured values were 0.715. Our retrieval and measuring methods presented in this paper accurately reflect field conditions. We suggest that this method is useful to describe shelterbelt structure using remote sensing.展开更多
This paper presents an efficient image feature representation method, namely angle structure descriptor(ASD), which is built based on the angle structures of images. According to the diversity in directions, angle str...This paper presents an efficient image feature representation method, namely angle structure descriptor(ASD), which is built based on the angle structures of images. According to the diversity in directions, angle structures are defined in local blocks. Combining color information in HSV color space, we use angle structures to detect images. The internal correlations between neighboring pixels in angle structures are explored to form a feature vector. With angle structures as bridges, ASD extracts image features by integrating multiple information as a whole, such as color, texture, shape and spatial layout information. In addition, the proposed algorithm is efficient for image retrieval without any clustering implementation or model training. Experimental results demonstrate that ASD outperforms the other related algorithms.展开更多
Passive Fourier transform infrared （FTIR） remote sensing measurement of chemical gas cloud is a vital technology. It takes an important part in many fields for the detection of released gases. The principle of conce...Passive Fourier transform infrared （FTIR） remote sensing measurement of chemical gas cloud is a vital technology. It takes an important part in many fields for the detection of released gases. The principle of concentration measurement is based on the Beer-Lambert law. Unlike the active measurement, for the passive remote sensing, in most cases, the difference between the temperature of the gas cloud and the brightness temperature of the background is usually a few kelvins. The gas cloud emission is almost equal to the background emission, thereby the emission of the gas cloud cannot be ignored. The concentration retrieval algorithm is quite different from the active measurement. In this paper, the concentration retrieval algorithm for the passive FTIR remote measurement of gas cloud is presented in detail, which involves radiative transfer model, radiometric calibration, absorption coefficient calculation, et al. The background spectrum has a broad feature, which is a slowly varying function of frequency. In this paper, the background spectrum is fitted with a polynomial by using the Levenberg-Marquardt method which is a kind of nonlinear least squares fitting algorithm. No background spectra are required. Thus, this method allows mobile, real-time and fast measurements of gas clouds.展开更多
As a typical technology for optical encryption,phase retrieval algorithms have been widely used in optical information encryption and authentication systems.This paper presents three applications of two-dimensional(2D...As a typical technology for optical encryption,phase retrieval algorithms have been widely used in optical information encryption and authentication systems.This paper presents three applications of two-dimensional(2D)phase retrieval for optical encryption and authentication:first,a hierarchical image encryption system,by which multiple images can be hidden into cascaded multiple phase masks;second,a multilevel image authentication system,which combines(t,n)threshold secret sharing(both t and n are positive integers,and t≤n)and phase retrieval,and provides both high-level and low-level authentication;and finally,a hierarchical multilevel authentication system that combines the secret sharing scheme based on basic vector operations and the phase retrieval,by which more certification images can be encoded into multiple cascaded phase masks of different hierarchical levels.These three phase retrieval algorithms can effectively illustrate phase-retrievalbased optical information security.The principles and features of each phase-retrieval-based optical security method are analyzed and discussed.It is hoped that this review will illustrate the current development of phase retrieval algorithms for optical information security and will also shed light on the future development of phase retrieval algorithms for optical information security.展开更多
Scatterometer is an instrument which provides all-day and large-scale wind field information, and its application especially to wind retrieval always attracts meteorologists. Certain reasons cause large direction erro...Scatterometer is an instrument which provides all-day and large-scale wind field information, and its application especially to wind retrieval always attracts meteorologists. Certain reasons cause large direction error, so it is important to find where the error mainly comes. Does it mainly result from the background field, the normalized radar cross-section （NRCS） or the method of wind retrieval？ It is valuable to research. First, depending on SDP2.0, the simulated ＇true＇ NRCS is calculated from the simulated ＇true＇ wind through the geophysical mode] function NSCAT2. The simulated background field is configured by adding a noise to the simulated ＇true＇ wind with the non-divergence constraint. Also, the simulated ＇measured＇ NRCS is formed by adding a noise to the simulated ＇true＇ NRCS. Then, the sensitivity experiments are taken, and the new method of regularization is used to improve the ambiguity removal with simulation experiments. The results show that the accuracy of wind retrieval is more sensitive to the noise in the background than in the measured NRCS; compared with the two-dimensional variational （2DVAR） ambiguity removal method, the accuracy of wind retrieval can be improved with the new method of Tikhonov regularization through choosing an appropriate regularization parameter, especially for the case of large error in the background. The work will provide important information and a new method for the wind retrieval with real data.展开更多
A new information search model is reported and the design and implementation of a system based on intelligent agent is presented. The system is an assistant information retrieval system which helps users to search wha...A new information search model is reported and the design and implementation of a system based on intelligent agent is presented. The system is an assistant information retrieval system which helps users to search what they need. The system consists of four main components: interface agent, information retrieval agent, broker agent and learning agent. They collaborate to implement system functions. The agents apply learning mechanisms based on an improved ID3 algorithm.展开更多
Coherent diffractive imaging （CDI） is a lensless imaging technique and can achieve a resolution beyond the Rayleigh or Abbe limit. The ptychographical iterative engine （PIE） is a CDI phase retrieval algorithm that...Coherent diffractive imaging （CDI） is a lensless imaging technique and can achieve a resolution beyond the Rayleigh or Abbe limit. The ptychographical iterative engine （PIE） is a CDI phase retrieval algorithm that uses multiple diffraction patterns obtained through the scan of a localized illumination on the specimen, which has been demonstrated successfully at optical and X-ray wavelengths. In this paper, a general PIE algorithm （gPIE） is presented and demonstrated with an He-Ne laser light diffraction dataset. This algorithm not only permits the removal of the accurate model of the illumination function in PIE, but also provides improved convergence speed and retrieval quality.展开更多
Grating-based X-ray phase contrast imaging has been demonstrated to he an extremely powerful phase-sensitive imaging technique. By using two-dimensional （2D） gratings, the observable contrast is extended to two refr...Grating-based X-ray phase contrast imaging has been demonstrated to he an extremely powerful phase-sensitive imaging technique. By using two-dimensional （2D） gratings, the observable contrast is extended to two refraction directions. Recently, we have developed a novel reverse-projection （RP） method, which is capable of retrieving the object information efficiently with one-dimensional （1D） grating-based phase contrast imaging. In this contribution, we present its extension to the 2D grating-based X-ray phase contrast imaging, named the two-dimensional reverse- projection （2D-RP） method, for information retrieval. The method takes into account the nonlinear contributions of two refraction directions and allows the retrieval of the absorption, the horizontal and the vertical refraction images. The obtained information can be used for the reconstruction of the three-dimensionak phase gradient field, and for an improved phase map retrieval and reconstruction. Numerical experiments are carried out, and the results confirm the validity of the 2D-RP method.展开更多
Light detection and ranging(LiDAR)has contributed immensely to forest mapping and 3D tree modelling.From the perspective of data acquisition,the integration of LiDAR data from different platforms would enrich forest i...Light detection and ranging(LiDAR)has contributed immensely to forest mapping and 3D tree modelling.From the perspective of data acquisition,the integration of LiDAR data from different platforms would enrich forest information at the tree and plot levels.This research develops a general framework to integrate ground-based and UAV-LiDAR(ULS)data to better estimate tree parameters based on quantitative structure modelling(QSM).This is accomplished in three sequential steps.First,the ground-based/ULS LiDAR data were co-registered based on the local density peaks of the clustered canopy.Next,redundancy and noise were removed for the ground-based/ULS LiDAR data fusion.Finally,tree modeling and biophysical parameter retrieval were based on QSM.Experiments were performed for Backpack/Handheld/UAV-based multi-platform mobile LiDAR data of a subtropical forest,including poplar and dawn redwood species.Generally,ground-based/ULS LiDAR data fusion outperforms ground-based LiDAR with respect to tree parameter estimation compared to field data.The fusion-derived tree height,tree volume,and crown volume significantly improved by up to 9.01%,5.28%,and 18.61%,respectively,in terms of rRMSE.By contrast,the diameter at breast height(DBH)is the parameter that has the least benefits from fusion,and rRMSE remains approximately the same,because stems are already well sampled from ground data.Additionally,particularly for dense forests,the fusion-derived tree parameters were improved compared to those derived from ground-based LiDAR.Ground-based LiDAR can potentially be used to estimate tree parameters in low-stand-density forests,whereby the improvement owing to fusion is not significant.展开更多
In this research, a content-based image retrieval （CBIR） system for high resolution satellite images has been developed by using texture features. The proposed approach uses the local binary pattern （LBP） texture ...In this research, a content-based image retrieval （CBIR） system for high resolution satellite images has been developed by using texture features. The proposed approach uses the local binary pattern （LBP） texture feature and a block based scheme. The query and database images are divided into equally sized blocks, from which LBP histograms are extracted. The block histograms are then compared by using the Chi-square distance. Experimental results show that the LBP representation provides a powerful tool for high resolution satellite images （HRSI） retrieval.展开更多
A convolutional neural network is employed to retrieve the time-domain envelop and phase of few-cycle femtosecond pulses from transient-grating frequency-resolved optical gating(TG-FROG) traces.We use theoretically ge...A convolutional neural network is employed to retrieve the time-domain envelop and phase of few-cycle femtosecond pulses from transient-grating frequency-resolved optical gating(TG-FROG) traces.We use theoretically generated TGFROG traces to complete supervised trainings of the convolutional neural networks,then use similarly generated traces not included in the training dataset to test how well the networks are trained.Accurate retrieval of such traces by the neural network is realized.In our case,we find that networks with exponential linear unit(ELU) activation function perform better than those with leaky rectified linear unit(LRELU) and scaled exponential linear unit(SELU).Finally,the issues that need to be addressed for the retrieval of experimental data by this method are discussed.展开更多
Due to its characteristics distribution and virtualization, cloud storage also brings new security problems. User＇s data is stored in the cloud, which separated the ownership from management. How to ensure the securi...Due to its characteristics distribution and virtualization, cloud storage also brings new security problems. User＇s data is stored in the cloud, which separated the ownership from management. How to ensure the security of cloud data, how to increase data availability and how to improve user privacy perception are the key issues of cloud storage research, especially when the cloud service provider is not completely trusted. In this paper, a cloud storage ciphertext retrieval scheme based on AES and homomorphic encryption is presented. This ciphertext retrieval scheme will not only conceal the user retrieval information, but also prevent the cloud from obtaining user access pattern such as read-write mode, and access frequency, thereby ensuring the safety of the ciphertext retrieval and user privacy. The results of simulation analysis show that the performance of this ciphertext retrieval scheme requires less overhead than other schemes on the same security level.展开更多
In medical research and clinical diagnosis, automated or computer-assisted classification and retrieval methods are highly desirable to offset the high cost of manual classification and manipulation by medical experts...In medical research and clinical diagnosis, automated or computer-assisted classification and retrieval methods are highly desirable to offset the high cost of manual classification and manipulation by medical experts. To facilitate the decision-making in the health-care and the related areas, in this paper, a two-step content-based medical image retrieval algorithm is proposed. Firstly, in the preprocessing step, the image segmentation is performed to distinguish image objects, and on the basis of the ...展开更多
Space debris retrieval problem utilizing a tethered system in an elliptical orbit is studied in this paper.An analytical control law specified by a tether length rate for retrieval is derived from a dumbbell model of ...Space debris retrieval problem utilizing a tethered system in an elliptical orbit is studied in this paper.An analytical control law specified by a tether length rate for retrieval is derived from a dumbbell model of the system.The proposed control method can suppress large swings around the local vertical position of the tethered system.Under such a control strategy,the debris retrieval behaves in asymptotic stable motion towards the expected angle.The stability of the non-autonomous system during the retrieval control is analyzed using the Floquet theory.The result demonstrates that an orbital region exists,on which the retrieval process maintains asymptotically stable.The proposed analytical control law is validated via numerical simulations.展开更多
Lung medical image retrieval based on content similarity plays an important role in computer-aided diagnosis of lung cancer.In recent years,binary hashing has become a hot topic in this field due to its compressed sto...Lung medical image retrieval based on content similarity plays an important role in computer-aided diagnosis of lung cancer.In recent years,binary hashing has become a hot topic in this field due to its compressed storage and fast query speed.Traditional hashing methods often rely on highdimensional features based hand-crafted methods,which might not be optimally compatible with lung nodule images.Also,different hashing bits contribute to the image retrieval differently,and therefore treating the hashing bits equally affects the retrieval accuracy.Hence,an image retrieval method of lung nodule images is proposed with the basis on convolutional neural networks and hashing.First,apre-trained and fine-tuned convolutional neural network is employed to learn multilevel semantic features of the lung nodules.Principal components analysis is utilized to remove redundant information and preserve informative semantic features of the lung nodules.Second,the proposed method relies on nine sign labels of lung nodules for the training set,and the semantic feature is combined to construct hashing functions.Finally,returned lung nodule images can be easily ranked with the query-adaptive search method based on weighted Hamming distance.Extensive experiments and evaluations on the dataset demonstrate that the proposed method can significantly improve the expression ability of lung nodule images,which further validates the effectiveness of the proposed method.展开更多
Aiming at shortcomings of traditional image retrieval systems, a new image retrieval approach based on color features of image combining intuitive fuzzy theory with genetic algorithm is proposed. Each image is segment...Aiming at shortcomings of traditional image retrieval systems, a new image retrieval approach based on color features of image combining intuitive fuzzy theory with genetic algorithm is proposed. Each image is segmented into a constant number of sub-images in vertical direction. Color features are extracted from every sub-image to get chromosome coding. It is considered that fuzzy membership and intuitive fuzzy hesitancy degree of every pixel＇s color in image are associated to all the color histogram bins. Certain feature, fuzzy feature and intuitive fuzzy feature of colors in an image, are used together to describe the content of image. Efficient combinations of sub-image are selected according to operation of selecting, crossing and variation. Retrieval results are obtained from image matching based on these color feature combinations of sub-images. Tests show that this approach can improve the accuracy of image retrieval in the case of not decreasing the speed of image retrieval. Its mean precision is above 80 %.展开更多
文摘Crime scene investigation(CSI)image is key evidence carrier during criminal investiga-tion,in which CSI image retrieval can assist the public police to obtain criminal clues.Moreover,with the rapid development of deep learning,data-driven paradigm has become the mainstreammethod of CSI image feature extraction and representation,and in this process,datasets provideeffective support for CSI retrieval performance.However,there is a lack of systematic research onCSI image retrieval methods and datasets.Therefore,we present an overview of the existing worksabout one-class and multi-class CSI image retrieval based on deep learning.According to theresearch,based on their technical functionalities and implementation methods,CSI image retrievalis roughly classified into five categories:feature representation,metric learning,generative adversar-ial networks,autoencoder networks and attention networks.Furthermore,We analyzed the remain-ing challenges and discussed future work directions in this field.
基金Project supported by the National Natural Science Foundation of China (Grant No. 40775023)
文摘According to the conclusion of the simulation experiments in paper I, the Tikhonov regularization method is applied to cyclone wind retrieval with a rain-effect-considering geophysical model function （called CMF＋Rain）. The CMF＋Rain model which is based on the NASA scatterometer-2 （NSCAT2） GMF is presented to compensate for the effects of rain on cyclone wind retrieval. With the multiple solution scheme （MSS）, the noise of wind retrieval is effectively suppressed, but the influence of the background increases. It will cause a large wind direction error in ambiguity removal when the background error is large. However, this can be mitigated by the new ambiguity removal method of Tikhonov regularization as proved in the simulation experiments. A case study on an extratropical cyclone of hurricane observed with SeaWinds at 25-km resolution shows that the retrieved wind speed for areas with rain is in better agreement with that derived from the best track analysis for the GMF＋Rain model, but the wind direction obtained with the two-dimensional variational （2DVAR） ambiguity removal is incorrect. The new method of Tikhonov regularization effectively improves the performance of wind direction ambiguity removal through choosing appropriate regularization parameters and the retrieved wind speed is almost the same as that obtained from the 2DVAR.
基金Supported by the National Defence Research Foundation(41234)
文摘In order to improve the utilization ratio of knowledge retrieval, a product-design knowledge retrieval approach based on ontology is proposed. A representation model of product-design knowledge is proposed according to its characteristics. Domain ontology of product-design is estab- lished and the semantic annotation technology is used to connect the design knowledge and ontolo- gy. A new semantic annotation format is developed and semantic information of the design knowl- edge is enriched by making use of ontology. On that basis a retrieval algorithm is designed for semantic retrieval. Finally, this approach is used in a knowledge management system for military-vehi- cle design and its effectiveness and feasibility are validated. Results show that the recall ratio and the precision ratio of knowledge retrieval are improved greatly and users＇ requirements in semantic retrieval are satisfied.
文摘A hybrid model that is based on the Combination of keywords and concept was put forward. The hybrid model is built on vector space model and probabilistic reasoning network. It not only can exert the advantages of keywords retrieval and concept retrieval but also can compensate for their shortcomings. Their parameters can be adjusted according to different usage in order to accept the best information retrieval result, and it has been proved by our experiments.
基金supported by the High-level Personnel Scientific Research Project in North China Institute of Water Resources and Electric Power (No. 201207)the Knowledge Innovation Program of the Chinese Academy Sciences (No. KZCX1-YW-08-02-01)the National Natural Science Foundation of China (No. 41101373)
文摘Shelterbelts are important in defending against natural disaster and maintaining ecological balances in farmland. Understanding of the shelterbelt vegetation fraction is fundamental to regional research of shelterbelts using remote sensing. We used SPOT5 imagery with 10×10m spatial resolution in combination with knowledge of the characteristics of shelterbelts to develop a method for retrieval of the vegetation fraction of shelterbelts by the pixel un-mixing model. We then used the method to retrieve values for shelterbelts in study area. By combining the parameters of photographic images with characteristics of shelterbelts, we developed a method for measuring the vegetation fraction of shelterbelts based on an advanced photographic method. We then measured the actual values to validate the retrieval result. The multiple correlation coefficients between the retrieved and measured values were 0.715. Our retrieval and measuring methods presented in this paper accurately reflect field conditions. We suggest that this method is useful to describe shelterbelt structure using remote sensing.
基金supported by the National Natural Science Foundation of China (No.61170145, 61373081, 61402268, 61401260, 61572298)the Technology and Development Project of Shandong (No.2013GGX10125)+1 种基金the Natural Science Foundation of Shandong China (No.BS2014DX006, ZR2014FM012)the Taishan Scholar Project of Shandong, China
文摘This paper presents an efficient image feature representation method, namely angle structure descriptor(ASD), which is built based on the angle structures of images. According to the diversity in directions, angle structures are defined in local blocks. Combining color information in HSV color space, we use angle structures to detect images. The internal correlations between neighboring pixels in angle structures are explored to form a feature vector. With angle structures as bridges, ASD extracts image features by integrating multiple information as a whole, such as color, texture, shape and spatial layout information. In addition, the proposed algorithm is efficient for image retrieval without any clustering implementation or model training. Experimental results demonstrate that ASD outperforms the other related algorithms.
基金Project supported by the National Natural Science Foundation of China (Grant No 083H311501)the National High Technology Research and Development Program of China (Grant No 073H3f1514)
文摘Passive Fourier transform infrared （FTIR） remote sensing measurement of chemical gas cloud is a vital technology. It takes an important part in many fields for the detection of released gases. The principle of concentration measurement is based on the Beer-Lambert law. Unlike the active measurement, for the passive remote sensing, in most cases, the difference between the temperature of the gas cloud and the brightness temperature of the background is usually a few kelvins. The gas cloud emission is almost equal to the background emission, thereby the emission of the gas cloud cannot be ignored. The concentration retrieval algorithm is quite different from the active measurement. In this paper, the concentration retrieval algorithm for the passive FTIR remote measurement of gas cloud is presented in detail, which involves radiative transfer model, radiometric calibration, absorption coefficient calculation, et al. The background spectrum has a broad feature, which is a slowly varying function of frequency. In this paper, the background spectrum is fitted with a polynomial by using the Levenberg-Marquardt method which is a kind of nonlinear least squares fitting algorithm. No background spectra are required. Thus, this method allows mobile, real-time and fast measurements of gas clouds.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61775121,61605165,61307003,61405122,and 11574311)the Key Research and Development Program of Shandong Province,China(Grant No.2018GGX101002)+1 种基金the Natural Science Foundation of Shandong Province,China(Grant No.ZR2019QF006)the Fundamental Research Funds of Shandong University,China(Grant No.2015GN031)
文摘As a typical technology for optical encryption,phase retrieval algorithms have been widely used in optical information encryption and authentication systems.This paper presents three applications of two-dimensional(2D)phase retrieval for optical encryption and authentication:first,a hierarchical image encryption system,by which multiple images can be hidden into cascaded multiple phase masks;second,a multilevel image authentication system,which combines(t,n)threshold secret sharing(both t and n are positive integers,and t≤n)and phase retrieval,and provides both high-level and low-level authentication;and finally,a hierarchical multilevel authentication system that combines the secret sharing scheme based on basic vector operations and the phase retrieval,by which more certification images can be encoded into multiple cascaded phase masks of different hierarchical levels.These three phase retrieval algorithms can effectively illustrate phase-retrievalbased optical information security.The principles and features of each phase-retrieval-based optical security method are analyzed and discussed.It is hoped that this review will illustrate the current development of phase retrieval algorithms for optical information security and will also shed light on the future development of phase retrieval algorithms for optical information security.
基金supported by the National Natural Science Foundation of China (Grant No. 40775023)
文摘Scatterometer is an instrument which provides all-day and large-scale wind field information, and its application especially to wind retrieval always attracts meteorologists. Certain reasons cause large direction error, so it is important to find where the error mainly comes. Does it mainly result from the background field, the normalized radar cross-section （NRCS） or the method of wind retrieval？ It is valuable to research. First, depending on SDP2.0, the simulated ＇true＇ NRCS is calculated from the simulated ＇true＇ wind through the geophysical mode] function NSCAT2. The simulated background field is configured by adding a noise to the simulated ＇true＇ wind with the non-divergence constraint. Also, the simulated ＇measured＇ NRCS is formed by adding a noise to the simulated ＇true＇ NRCS. Then, the sensitivity experiments are taken, and the new method of regularization is used to improve the ambiguity removal with simulation experiments. The results show that the accuracy of wind retrieval is more sensitive to the noise in the background than in the measured NRCS; compared with the two-dimensional variational （2DVAR） ambiguity removal method, the accuracy of wind retrieval can be improved with the new method of Tikhonov regularization through choosing an appropriate regularization parameter, especially for the case of large error in the background. The work will provide important information and a new method for the wind retrieval with real data.
文摘A new information search model is reported and the design and implementation of a system based on intelligent agent is presented. The system is an assistant information retrieval system which helps users to search what they need. The system consists of four main components: interface agent, information retrieval agent, broker agent and learning agent. They collaborate to implement system functions. The agents apply learning mechanisms based on an improved ID3 algorithm.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 11179009 and 50875013)the Beijing Municipal Natural Science Foundation, China (Grant No. 4102036)the Beijing NOVA Program, China (Grant No. 2009A09)
文摘Coherent diffractive imaging （CDI） is a lensless imaging technique and can achieve a resolution beyond the Rayleigh or Abbe limit. The ptychographical iterative engine （PIE） is a CDI phase retrieval algorithm that uses multiple diffraction patterns obtained through the scan of a localized illumination on the specimen, which has been demonstrated successfully at optical and X-ray wavelengths. In this paper, a general PIE algorithm （gPIE） is presented and demonstrated with an He-Ne laser light diffraction dataset. This algorithm not only permits the removal of the accurate model of the illumination function in PIE, but also provides improved convergence speed and retrieval quality.
基金Project supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No.KJCX2-YW-N42)the Key Project of the National Natural Science Foundation of China (Grant No.10734070)+3 种基金the National Natural Science Foundation of China (Grant No.11205157)the National Basic Research Program of China (Grant Nos. 2009CB930804 and 2012CB825800)the Fundamental Research Funds for the Central Universities,China (Grant No. WK2310000021)the China Postdoctoral Science Foundation (Grant No. 2011M501064)
文摘Grating-based X-ray phase contrast imaging has been demonstrated to he an extremely powerful phase-sensitive imaging technique. By using two-dimensional （2D） gratings, the observable contrast is extended to two refraction directions. Recently, we have developed a novel reverse-projection （RP） method, which is capable of retrieving the object information efficiently with one-dimensional （1D） grating-based phase contrast imaging. In this contribution, we present its extension to the 2D grating-based X-ray phase contrast imaging, named the two-dimensional reverse- projection （2D-RP） method, for information retrieval. The method takes into account the nonlinear contributions of two refraction directions and allows the retrieval of the absorption, the horizontal and the vertical refraction images. The obtained information can be used for the reconstruction of the three-dimensionak phase gradient field, and for an improved phase map retrieval and reconstruction. Numerical experiments are carried out, and the results confirm the validity of the 2D-RP method.
基金supported by the National Natural Science Foundation of China(Project No.42171361)the Research Grants Council of the Hong Kong Special Administrative Region,China,under Project PolyU 25211819the Hong Kong Polytechnic University under Projects 1-ZE8E and 1-ZVN6.
文摘Light detection and ranging(LiDAR)has contributed immensely to forest mapping and 3D tree modelling.From the perspective of data acquisition,the integration of LiDAR data from different platforms would enrich forest information at the tree and plot levels.This research develops a general framework to integrate ground-based and UAV-LiDAR(ULS)data to better estimate tree parameters based on quantitative structure modelling(QSM).This is accomplished in three sequential steps.First,the ground-based/ULS LiDAR data were co-registered based on the local density peaks of the clustered canopy.Next,redundancy and noise were removed for the ground-based/ULS LiDAR data fusion.Finally,tree modeling and biophysical parameter retrieval were based on QSM.Experiments were performed for Backpack/Handheld/UAV-based multi-platform mobile LiDAR data of a subtropical forest,including poplar and dawn redwood species.Generally,ground-based/ULS LiDAR data fusion outperforms ground-based LiDAR with respect to tree parameter estimation compared to field data.The fusion-derived tree height,tree volume,and crown volume significantly improved by up to 9.01%,5.28%,and 18.61%,respectively,in terms of rRMSE.By contrast,the diameter at breast height(DBH)is the parameter that has the least benefits from fusion,and rRMSE remains approximately the same,because stems are already well sampled from ground data.Additionally,particularly for dense forests,the fusion-derived tree parameters were improved compared to those derived from ground-based LiDAR.Ground-based LiDAR can potentially be used to estimate tree parameters in low-stand-density forests,whereby the improvement owing to fusion is not significant.
文摘In this research, a content-based image retrieval （CBIR） system for high resolution satellite images has been developed by using texture features. The proposed approach uses the local binary pattern （LBP） texture feature and a block based scheme. The query and database images are divided into equally sized blocks, from which LBP histograms are extracted. The block histograms are then compared by using the Chi-square distance. Experimental results show that the LBP representation provides a powerful tool for high resolution satellite images （HRSI） retrieval.
基金Project supported by the National Key R&D Program of China(Grant No.2017YFB0405202)the National Natural Science Foundation of China(Grant Nos.61690221,91850209,and 11774277)。
文摘A convolutional neural network is employed to retrieve the time-domain envelop and phase of few-cycle femtosecond pulses from transient-grating frequency-resolved optical gating(TG-FROG) traces.We use theoretically generated TGFROG traces to complete supervised trainings of the convolutional neural networks,then use similarly generated traces not included in the training dataset to test how well the networks are trained.Accurate retrieval of such traces by the neural network is realized.In our case,we find that networks with exponential linear unit(ELU) activation function perform better than those with leaky rectified linear unit(LRELU) and scaled exponential linear unit(SELU).Finally,the issues that need to be addressed for the retrieval of experimental data by this method are discussed.
基金the National Natural Science Foundation of China under Grant，the Fundamental Research Funds for the Central Universities under Grant No.FRF-TP-14-046A2
文摘Due to its characteristics distribution and virtualization, cloud storage also brings new security problems. User＇s data is stored in the cloud, which separated the ownership from management. How to ensure the security of cloud data, how to increase data availability and how to improve user privacy perception are the key issues of cloud storage research, especially when the cloud service provider is not completely trusted. In this paper, a cloud storage ciphertext retrieval scheme based on AES and homomorphic encryption is presented. This ciphertext retrieval scheme will not only conceal the user retrieval information, but also prevent the cloud from obtaining user access pattern such as read-write mode, and access frequency, thereby ensuring the safety of the ciphertext retrieval and user privacy. The results of simulation analysis show that the performance of this ciphertext retrieval scheme requires less overhead than other schemes on the same security level.
文摘In medical research and clinical diagnosis, automated or computer-assisted classification and retrieval methods are highly desirable to offset the high cost of manual classification and manipulation by medical experts. To facilitate the decision-making in the health-care and the related areas, in this paper, a two-step content-based medical image retrieval algorithm is proposed. Firstly, in the preprocessing step, the image segmentation is performed to distinguish image objects, and on the basis of the ...
基金Supported by the Natural Science Foundation of China(11672125)the Fundamental Research Funds for the Central Universities(NS2016009)
文摘Space debris retrieval problem utilizing a tethered system in an elliptical orbit is studied in this paper.An analytical control law specified by a tether length rate for retrieval is derived from a dumbbell model of the system.The proposed control method can suppress large swings around the local vertical position of the tethered system.Under such a control strategy,the debris retrieval behaves in asymptotic stable motion towards the expected angle.The stability of the non-autonomous system during the retrieval control is analyzed using the Floquet theory.The result demonstrates that an orbital region exists,on which the retrieval process maintains asymptotically stable.The proposed analytical control law is validated via numerical simulations.
基金Supported by the National Natural Science Foundation of China(61373100)the Open Funding Project of State Key Laboratory of Virtual Reality Technology and Systems(BUAA-VR-16KF-13,BUAA-VR-17KF-14,BUAA-VR-17KF-15)the Research Project Supported by Shanxi Scholarship Council of China(2016-038)
文摘Lung medical image retrieval based on content similarity plays an important role in computer-aided diagnosis of lung cancer.In recent years,binary hashing has become a hot topic in this field due to its compressed storage and fast query speed.Traditional hashing methods often rely on highdimensional features based hand-crafted methods,which might not be optimally compatible with lung nodule images.Also,different hashing bits contribute to the image retrieval differently,and therefore treating the hashing bits equally affects the retrieval accuracy.Hence,an image retrieval method of lung nodule images is proposed with the basis on convolutional neural networks and hashing.First,apre-trained and fine-tuned convolutional neural network is employed to learn multilevel semantic features of the lung nodules.Principal components analysis is utilized to remove redundant information and preserve informative semantic features of the lung nodules.Second,the proposed method relies on nine sign labels of lung nodules for the training set,and the semantic feature is combined to construct hashing functions.Finally,returned lung nodule images can be easily ranked with the query-adaptive search method based on weighted Hamming distance.Extensive experiments and evaluations on the dataset demonstrate that the proposed method can significantly improve the expression ability of lung nodule images,which further validates the effectiveness of the proposed method.
基金Sponsored by the Ministerial Level Foundation(20061823)
文摘Aiming at shortcomings of traditional image retrieval systems, a new image retrieval approach based on color features of image combining intuitive fuzzy theory with genetic algorithm is proposed. Each image is segmented into a constant number of sub-images in vertical direction. Color features are extracted from every sub-image to get chromosome coding. It is considered that fuzzy membership and intuitive fuzzy hesitancy degree of every pixel＇s color in image are associated to all the color histogram bins. Certain feature, fuzzy feature and intuitive fuzzy feature of colors in an image, are used together to describe the content of image. Efficient combinations of sub-image are selected according to operation of selecting, crossing and variation. Retrieval results are obtained from image matching based on these color feature combinations of sub-images. Tests show that this approach can improve the accuracy of image retrieval in the case of not decreasing the speed of image retrieval. Its mean precision is above 80 %.
