One of the main drawbacks of Digital Holography(DH)is the coherent nature of the light source,which severely corrupts the quality of holographic reconstructions.Although numerous techniques to reduce noise in DH have ...One of the main drawbacks of Digital Holography(DH)is the coherent nature of the light source,which severely corrupts the quality of holographic reconstructions.Although numerous techniques to reduce noise in DH have provided good results,holographic noise suppression remains a challenging task.We propose a novel framework that combines the concepts of encoding multiple uncorrelated digital holograms,block grouping and collaborative filtering to achieve quasi noise-free DH reconstructions.The optimized joint action of these different image-denoising methods permits the removal of up to 98%of the noise while preserving the image contrast.The resulting quality of the hologram reconstructions is comparable to the quality achievable with non-coherent techniques and far beyond the current state of art in DH.Experimental validation is provided for both singlewavelength and multi-wavelength DH,and a comparison with the most used holographic denoising methods is performed.展开更多
Annular subaperture interferometry （ASI） has been developed for low cost and flexible test of rotationally symmetric aspheric surfaces, in which accurately combining the subaperture measurement data corrupted by mis...Annular subaperture interferometry （ASI） has been developed for low cost and flexible test of rotationally symmetric aspheric surfaces, in which accurately combining the subaperture measurement data corrupted by misalignments and noise into a complete surface figure is the key problem. By introducing the Zernike annular polynomials which are orthogonal over annulus, a method that eliminates the coupling problem in the earlier algorithm based on Zernike circle polynomials is proposed. Vector-matrix notation is used to simplify the description and calculations. The performance of this reduction method is evaluated by numerical simulation. The results prove this method with high precision and good anti-noise capability.展开更多
The forecasting of the demand applied to water supply systems has been an important tool to realize time control. The use of the time series to do the forecasting of the demand is the main way that has been used by re...The forecasting of the demand applied to water supply systems has been an important tool to realize time control. The use of the time series to do the forecasting of the demand is the main way that has been used by researchers. By this way, the need of a complete time demand series increases. This work presents two ways to reconstruct the water demand time series synthetically, using the Average Reconstruction Method and Fourier Method. Both the methods were considered interesting to do the synthetic reconstruction and able to complete the time series, but the Fourier Method showed better results and a better fitness to approximation of the water consumption pattern.展开更多
The 3D reconstruction using deep learning-based intelligent systems can provide great help for measuring an individual’s height and shape quickly and accurately through 2D motion-blurred images.Generally,during the a...The 3D reconstruction using deep learning-based intelligent systems can provide great help for measuring an individual’s height and shape quickly and accurately through 2D motion-blurred images.Generally,during the acquisition of images in real-time,motion blur,caused by camera shaking or human motion,appears.Deep learning-based intelligent control applied in vision can help us solve the problem.To this end,we propose a 3D reconstruction method for motion-blurred images using deep learning.First,we develop a BF-WGAN algorithm that combines the bilateral filtering(BF)denoising theory with a Wasserstein generative adversarial network(WGAN)to remove motion blur.The bilateral filter denoising algorithm is used to remove the noise and to retain the details of the blurred image.Then,the blurred image and the corresponding sharp image are input into the WGAN.This algorithm distinguishes the motion-blurred image from the corresponding sharp image according to the WGAN loss and perceptual loss functions.Next,we use the deblurred images generated by the BFWGAN algorithm for 3D reconstruction.We propose a threshold optimization random sample consensus(TO-RANSAC)algorithm that can remove the wrong relationship between two views in the 3D reconstructed model relatively accurately.Compared with the traditional RANSAC algorithm,the TO-RANSAC algorithm can adjust the threshold adaptively,which improves the accuracy of the 3D reconstruction results.The experimental results show that our BF-WGAN algorithm has a better deblurring effect and higher efficiency than do other representative algorithms.In addition,the TO-RANSAC algorithm yields a calculation accuracy considerably higher than that of the traditional RANSAC algorithm.展开更多
This paper presents a method to deal with an extension of regional gradient observability developed for parabolic system [1,2] to hyperbolic one. This concerns the reconstruction of the state gradient only on a subreg...This paper presents a method to deal with an extension of regional gradient observability developed for parabolic system [1,2] to hyperbolic one. This concerns the reconstruction of the state gradient only on a subregion of the system domain. Then necessary conditions for sensors structure are established in order to obtain regional gradient observability. An approach is developed which allows the reconstruction of the system state gradient on a given subregion. The obtained results are illustrated by numerical examples and simulations.展开更多
The aim of this work is to study the notion of the gradient observability on a subregion?ω of the evolution domain?Ω for a class of semilinear hyperbolic systems. We show, under some hypothesis, that the gradient re...The aim of this work is to study the notion of the gradient observability on a subregion?ω of the evolution domain?Ω for a class of semilinear hyperbolic systems. We show, under some hypothesis, that the gradient reconstruction is achieved following sectorial approach combined with fixed point techniques. The obtained results lead to an algorithm which can be implemented numerically.展开更多
基金supported by DATABENC_Progetto SNECS-PON03PE_00163_1 Social Network delle Entitàdei Centri Storici.
文摘One of the main drawbacks of Digital Holography(DH)is the coherent nature of the light source,which severely corrupts the quality of holographic reconstructions.Although numerous techniques to reduce noise in DH have provided good results,holographic noise suppression remains a challenging task.We propose a novel framework that combines the concepts of encoding multiple uncorrelated digital holograms,block grouping and collaborative filtering to achieve quasi noise-free DH reconstructions.The optimized joint action of these different image-denoising methods permits the removal of up to 98%of the noise while preserving the image contrast.The resulting quality of the hologram reconstructions is comparable to the quality achievable with non-coherent techniques and far beyond the current state of art in DH.Experimental validation is provided for both singlewavelength and multi-wavelength DH,and a comparison with the most used holographic denoising methods is performed.
基金supported by the National Natural Science Foundation of China(6107116361071164+5 种基金6147119161501233)the Fundamental Research Funds for the Central Universities(NP2014504)the Aeronautical Science Foundation(20152052026)the Electronic & Information School of Yangtze University Innovation Foundation(2016-DXCX-05)the Priority Academic Program Development of Jiangsu Higher Education Institutions
基金This work was supported by the National "863" Project of China.
文摘Annular subaperture interferometry （ASI） has been developed for low cost and flexible test of rotationally symmetric aspheric surfaces, in which accurately combining the subaperture measurement data corrupted by misalignments and noise into a complete surface figure is the key problem. By introducing the Zernike annular polynomials which are orthogonal over annulus, a method that eliminates the coupling problem in the earlier algorithm based on Zernike circle polynomials is proposed. Vector-matrix notation is used to simplify the description and calculations. The performance of this reduction method is evaluated by numerical simulation. The results prove this method with high precision and good anti-noise capability.
文摘The forecasting of the demand applied to water supply systems has been an important tool to realize time control. The use of the time series to do the forecasting of the demand is the main way that has been used by researchers. By this way, the need of a complete time demand series increases. This work presents two ways to reconstruct the water demand time series synthetically, using the Average Reconstruction Method and Fourier Method. Both the methods were considered interesting to do the synthetic reconstruction and able to complete the time series, but the Fourier Method showed better results and a better fitness to approximation of the water consumption pattern.
基金the National Natural Science Foundation of China under Grant 61902311in part by the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(KAKENHI)under Grant JP18K18044.
文摘The 3D reconstruction using deep learning-based intelligent systems can provide great help for measuring an individual’s height and shape quickly and accurately through 2D motion-blurred images.Generally,during the acquisition of images in real-time,motion blur,caused by camera shaking or human motion,appears.Deep learning-based intelligent control applied in vision can help us solve the problem.To this end,we propose a 3D reconstruction method for motion-blurred images using deep learning.First,we develop a BF-WGAN algorithm that combines the bilateral filtering(BF)denoising theory with a Wasserstein generative adversarial network(WGAN)to remove motion blur.The bilateral filter denoising algorithm is used to remove the noise and to retain the details of the blurred image.Then,the blurred image and the corresponding sharp image are input into the WGAN.This algorithm distinguishes the motion-blurred image from the corresponding sharp image according to the WGAN loss and perceptual loss functions.Next,we use the deblurred images generated by the BFWGAN algorithm for 3D reconstruction.We propose a threshold optimization random sample consensus(TO-RANSAC)algorithm that can remove the wrong relationship between two views in the 3D reconstructed model relatively accurately.Compared with the traditional RANSAC algorithm,the TO-RANSAC algorithm can adjust the threshold adaptively,which improves the accuracy of the 3D reconstruction results.The experimental results show that our BF-WGAN algorithm has a better deblurring effect and higher efficiency than do other representative algorithms.In addition,the TO-RANSAC algorithm yields a calculation accuracy considerably higher than that of the traditional RANSAC algorithm.
文摘This paper presents a method to deal with an extension of regional gradient observability developed for parabolic system [1,2] to hyperbolic one. This concerns the reconstruction of the state gradient only on a subregion of the system domain. Then necessary conditions for sensors structure are established in order to obtain regional gradient observability. An approach is developed which allows the reconstruction of the system state gradient on a given subregion. The obtained results are illustrated by numerical examples and simulations.
文摘The aim of this work is to study the notion of the gradient observability on a subregion?ω of the evolution domain?Ω for a class of semilinear hyperbolic systems. We show, under some hypothesis, that the gradient reconstruction is achieved following sectorial approach combined with fixed point techniques. The obtained results lead to an algorithm which can be implemented numerically.
