Depth discontinuity edge affects the visual quality of synthesized images in 3D image warping.However,it suffers from accuracy degradation when up-sampled from low-resolution depth maps,especially at large scaling fac...Depth discontinuity edge affects the visual quality of synthesized images in 3D image warping.However,it suffers from accuracy degradation when up-sampled from low-resolution depth maps,especially at large scaling factors.To preserve the accuracy of depth discontinuity,a novel joint bilateral depth super-resolution with intensity guidance method is proposed.Particularly,the fast local intensity classification is exploited to estimate depth coefficients in joint bilateral up-sampling for depth maps,so as to eliminate depth discontinuity edge misalignment.Additionally,the proposed method is accelerated on graphic processing units(GPUs)to meet the requirement of realtime application.Experiments demonstrate that our method can preserve the accuracy of depth discontinuity edges after super resolution,leveraging the visual quality of synthesized image in 3D image warping.展开更多
Owing to the constraints of depth sensing technology,images acquired by depth cameras are inevitably mixed with various noises.For depth maps presented in gray values,this research proposes a novel denoising model,ter...Owing to the constraints of depth sensing technology,images acquired by depth cameras are inevitably mixed with various noises.For depth maps presented in gray values,this research proposes a novel denoising model,termed graph-based transform(GBT)and dual graph Laplacian regularization(DGLR)(DGLR-GBT).This model specifically aims to remove Gaussian white noise by capitalizing on the nonlocal self-similarity(NSS)and the piecewise smoothness properties intrinsic to depth maps.Within the group sparse coding(GSC)framework,a combination of GBT and DGLR is implemented.Firstly,within each group,the graph is constructed by using estimates of the true values of the averaged blocks instead of the observations.Secondly,the graph Laplacian regular terms are constructed based on rows and columns of similar block groups,respectively.Lastly,the solution is obtained effectively by combining the alternating direction multiplication method(ADMM)with the weighted thresholding method within the domain of GBT.展开更多
Least-squares migration （LSM） is applied to image subsurface structures and lithology by minimizing the objective function of the observed seismic and reverse-time migration residual data of various underground refl...Least-squares migration （LSM） is applied to image subsurface structures and lithology by minimizing the objective function of the observed seismic and reverse-time migration residual data of various underground reflectivity models. LSM reduces the migration artifacts, enhances the spatial resolution of the migrated images, and yields a more accurate subsurface reflectivity distribution than that of standard migration. The introduction of regularization constraints effectively improves the stability of the least-squares offset. The commonly used regularization terms are based on the L2-norm, which smooths the migration results, e.g., by smearing the reflectivities, while providing stability. However, in exploration geophysics, reflection structures based on velocity and density are generally observed to be discontinuous in depth, illustrating sparse reflectance. To obtain a sparse migration profile, we propose the super-resolution least-squares Kirchhoff prestack depth migration by solving the L0-norm-constrained optimization problem. Additionally, we introduce a two-stage iterative soft and hard thresholding algorithm to retrieve the super-resolution reflectivity distribution. Further, the proposed algorithm is applied to complex synthetic data. Furthermore, the sensitivity of the proposed algorithm to noise and the dominant frequency of the source wavelet was evaluated. Finally, we conclude that the proposed method improves the spatial resolution and achieves impulse-like reflectivity distribution and can be applied to structural interpretations and complex subsurface imaging.展开更多
Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil s...Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil spatial heterogeneity is high.In this study,we proposed an integrated method to select environmental covariates for predictive soil depth mapping.First,candidate variables that may influence the development of soil depth were selected based on pedogenetic knowledge.Second,three conventional methods(Pearson correlation analysis(PsCA),generalized additive models(GAMs),and Random Forest(RF))were used to generate optimal combinations of environmental covariates.Finally,three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental covariate.We tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China.A total of 129 soil sampling sites were collected using a representative sampling strategy,and RF and support vector machine(SVM)models were used to map soil depth.The results showed that compared to the set of environmental covariates selected by the three conventional selection methods,the set of environmental covariates selected by the proposed method achieved higher mapping accuracy.The combination from the proposed method obtained a root mean square error(RMSE)of 11.88 cm,which was 2.25–7.64 cm lower than the other methods,and an R^2 value of 0.76,which was 0.08–0.26 higher than the other methods.The results suggest that our method can be used as an alternative to the conventional methods for soil depth mapping and may also be effective for mapping other soil properties.展开更多
The depth information of the scene indicates the distance between the object and the camera,and depth extraction is a key technology in 3D video system.The emergence of Kinect makes the high resolution depth map captu...The depth information of the scene indicates the distance between the object and the camera,and depth extraction is a key technology in 3D video system.The emergence of Kinect makes the high resolution depth map capturing possible.However,the depth map captured by Kinect can not be directly used due to the existing holes and noises,which needs to be repaired.We propose a texture combined inpainting algorithm in this paper.Firstly,the foreground is segmented combined with the color characteristics of the texture image to repair the foreground of the depth map.Secondly,region growing is used to determine the match region of the hole in the depth map,and to accurately position the match region according to the texture information.Then the match region is weighted to fill the hole.Finally,a Gaussian filter is used to remove the noise in the depth map.Experimental results show that the proposed method can effectively repair the holes existing in the original depth map and get an accurate and smooth depth map,which can be used to render a virtual image with good quality.展开更多
Structured illumination microscopy(SIM)is a promising super-resolution technique for imaging subcellular structures and dynamics due to its compatibility with most commonly usedffuorescent labeling methods.Structured ...Structured illumination microscopy(SIM)is a promising super-resolution technique for imaging subcellular structures and dynamics due to its compatibility with most commonly usedffuorescent labeling methods.Structured illumination can be obtained by either laser interference or projection of fringe patterns.Here,we proposed a fringe projector composed of a compact multiwavelength LEDs module and a digital micromirror device(DMD)which can be directly attached to most commercial invertedffuorescent microscopes and update it into a SIM system.The effects of the period and duty cycle of fringe patterns on the modulation depth of the structured lightfield were studied.With the optimized fringe pattern,1:6×resolution improvement could be obtained with high-end oil objectives.Multicolor imaging and dynamics of subcellular organelles in live cells were also demonstrated.Our method provides a low-cost solution for SIM setup to expand its wide range of applications to most research labs in thefield of life science and medicine.展开更多
Not many bathymetric maps are available for many lakes and reservoirs in developing countries. Usually the bathymetric mapping requires investment in expensive equipment and fieldwork, both of which are not accessible...Not many bathymetric maps are available for many lakes and reservoirs in developing countries. Usually the bathymetric mapping requires investment in expensive equipment and fieldwork, both of which are not accessible in these countries. This work demonstrates the ability to develop bathymetric map of Mosul Lake by using a digital elevation model (DEM). The depths model of the lake was designed through the use of three main stages;a coastline extraction, dataset interpolation and a triangular irregular network model. The normalized difference water index (NDWI) was used for automatic delineation of the lake coastline from satellite images. The ordinary kriging interpolation with a stable model was used to interpolate the water depths dataset. Finally a triangulated irregular network (TIN) model was used to visualize the resulting interpolation model. Calculated values of area and volume of a TIN model during 2011 were compared with values of supposed initial operation of the reservoir. The differences of water volume storage between these stages at 321 m water level was about 0.81 × 109 m3, where the lake lost around 10% of storage value. Also the results of depths lake model show that the change in water storage between March and July 2011 was about 3.08 × 109 m3.展开更多
In the nondestructive testing and evaluation area,magnetic major hysteresis loop measurement technology are widely applied for ferromagnetic material evaluation.However the characterization ability of major hysteresis...In the nondestructive testing and evaluation area,magnetic major hysteresis loop measurement technology are widely applied for ferromagnetic material evaluation.However the characterization ability of major hysteresis loop measurement technology greatly varies as the evaluated target properties.To solve this limitation,magnetic minor hysteresis loops,which reflect the responses of ferromagnetic material magnetization in a systematic way,is recommend.Inspired by plenty of information carried by the minor loops,the sensitivity mapping technique was developed to achieve the highest sensitivity of minor-loop parameters to the nondestructively evaluated targets.In this study,for the first time,the sensitivity mapping technique is used to measure the tensile force in a steel strand and evaluate the effective case depth in induction-hardened steel rods.The method and procedures for the sensitivity mapping technique are given before experimental detection.The obtained experimental results indicate that the linear correlation between the induced voltage(or the magnetic induction intensity)and the tensile force(or effective case depth)exists at most of the locations in the cluster of minor loops.The obtained sensitivity maps can be used to optimize the applied magnetic field(or excitation current)and the analyzed locations at the minor loops for achieving the highest sensitivity.For the purpose of tensile force measurement,it is suggested that the strand should be firstly magnetized to the near-saturation state and then restored to the remanent state.In this way,the highest sensitivity is obtained as about 15.26 mV/kN.As for the induction-hardened steel rods,the highest sensitivity of magnetic induction intensity to the effective case depth occurs under low magnetic field conditions and the absolute value of the highest sensitivity is about 0.1110 T/mm.This indicates that if the highest sensitivity is required in the case depth evaluation,the induction-hardened steel rods are only required to be weakly magnetized.The proposed sensitivity mapping technique shows the good performance in the high-sensitivity evaluation of tensile force and case depth in ferromagnetic materials and its application scope can be extended to other nondestructive detection fields.展开更多
A maximum a posteriori（ MAP） algorithm is proposed to improve the accuracy of super resolution（ SR） reconstruction in traditional methods. The algorithm applies both joints image registration and SR reconstruction...A maximum a posteriori（ MAP） algorithm is proposed to improve the accuracy of super resolution（ SR） reconstruction in traditional methods. The algorithm applies both joints image registration and SR reconstruction in the framework,but separates them in the process of iteratiion. Firstly,we estimate the shifting parameters through two lowresolution（ LR） images and use the parameters to reconstruct initial HR images. Then,we update the shifting parameters using HR images. The aforementioned steps are repeated until the ideal HR images are obtained. The metrics such as PSNR and SSIM are used to fully evaluate the quality of the reconstructed image. Experimental results indicate that the proposed method can enhance image resolution efficiently.展开更多
Recognition of the human actions by computer vision has become an active research area in recent years. Due to the speed and the high similarity of the actions, the current algorithms cannot get high recognition rate....Recognition of the human actions by computer vision has become an active research area in recent years. Due to the speed and the high similarity of the actions, the current algorithms cannot get high recognition rate. A new recognition method of the human action is proposed with the multi-scale directed depth motion maps(MsdDMMs) and Log-Gabor filters. According to the difference between the speed and time order of an action, MsdDMMs is proposed under the energy framework. Meanwhile, Log-Gabor is utilized to describe the texture details of MsdDMMs for the motion characteristics. It can easily satisfy both the texture characterization and the visual features of human eye. Furthermore, the collaborative representation is employed as action recognition by the classification. Experimental results show that the proposed algorithm, which is applied in the MSRAction3 D dataset and MSRGesture3 D dataset, can achieve the accuracy of 95.79% and 96.43% respectively. It also has higher accuracy than the existing algorithms, such as super normal vector(SNV), hierarchical recurrent neural network(Hierarchical RNN).展开更多
This paper proposes a new technique that is used to embed depth maps into corresponding 2-dimensional （2D） images. Since a 2D image and its depth map are integrated into one type of image format, they can be treated...This paper proposes a new technique that is used to embed depth maps into corresponding 2-dimensional （2D） images. Since a 2D image and its depth map are integrated into one type of image format, they can be treated as if they were one 2D image. Thereby, it can reduce the amount of data in 3D images by half and simplify the processes for sending them through networks because the synchronization between images for the left and right eyes becomes unnecessary. We embed depth maps in the quantized discrete cosine transform （DCT） data of 2D images. The key to this technique is whether the depth maps could be embedded into 2D images without perceivably deteriorating their quality. We try to reduce their deterioration by compressing the depth map data by using the differences from the next pixel to the left. We assume that there is only one non-zero pixel at most on one horizontal line in the DCT block because the depth map values change abruptly. We conduct an experiment to evaluate the quality of the 2D images embedded with depth maps and find that satisfactory quality could be achieved.展开更多
A new method of super-resolution image reconstruction is proposed,which uses a three-step-training error backpropagation neural network(BPNN)to realize the super-resolution reconstruction(SRR)of satellite image.The me...A new method of super-resolution image reconstruction is proposed,which uses a three-step-training error backpropagation neural network(BPNN)to realize the super-resolution reconstruction(SRR)of satellite image.The method is based on BPNN.First,three groups learning samples with different resolutions are obtained according to image observation model,and then vector mappings are respectively used to those three group learning samples to speed up the convergence of BPNN,at last,three times consecutive training are carried on the BPNN.Training samples used in each step are of higher resolution than those used in the previous steps,so the increasing weights store a great amount of information for SRR,and network performance and generalization ability are improved greatly.Simulation and generalization tests are carried on the well-trained three-step-training NN respectively,and the reconstruction results with higher resolution images verify the effectiveness and validity of this method.展开更多
Generation of a depth-map from 2D video is the kernel of DIBR (Depth Image Based Rendering) in 2D-3D video conversion systems. However it occupies over most of the system resource where the motion search module takes ...Generation of a depth-map from 2D video is the kernel of DIBR (Depth Image Based Rendering) in 2D-3D video conversion systems. However it occupies over most of the system resource where the motion search module takes up 90% time-consuming in typical motion estimation-based depth-map generation algorithms. In order to reduce the computational complexity, in this paper a new fast depth-map generation algorithm based on motion search is developed, in which a fast diamond search algorithm is adopted to decide whether a 16x16 or 4x4 block size is used based on Sobel operator in the motion search module to obtain a sub-depth-map. Then the sub-depth-map will be fused with the sub-depth-maps gotten from depth from color component Cr and depth from linear perspective modules to compensate and refine detail of the depth-map, finally obtain a better depth-map. The simulation results demonstrate that the new approach can greatly reduce over 50% computational complexity compared to other existing methods.展开更多
Depth maps are used for synthesis virtual view in free-viewpoint television （FTV） systems. When depth maps are derived using existing depth estimation methods, the depth distortions will cause undesirable artifacts ...Depth maps are used for synthesis virtual view in free-viewpoint television （FTV） systems. When depth maps are derived using existing depth estimation methods, the depth distortions will cause undesirable artifacts in the synthesized views. To solve this problem, a 3D video quality model base depth maps （D-3DV） for virtual view synthesis and depth map coding in the FTV applications is proposed. First, the relationships between distortions in coded depth map and rendered view are derived. Then, a precisely 3DV quality model based depth characteristics is develop for the synthesized virtual views. Finally, based on D-3DV model, a multilateral filtering is applied as a pre-processed filter to reduce rendering artifacts. The experimental results evaluated by objective and subjective methods indicate that the proposed D-3DV model can reduce bit-rate of depth coding and achieve better rendering quality.展开更多
The creation of the 3D rendering model involves the prediction of an accurate depth map for the input images.A proposed approach of a modified semi-global block matching algorithm with variable window size and the gra...The creation of the 3D rendering model involves the prediction of an accurate depth map for the input images.A proposed approach of a modified semi-global block matching algorithm with variable window size and the gradient assessment of objects predicts the depth map.3D modeling and view synthesis algorithms could effectively handle the obtained disparity maps.This work uses the consistency check method to find an accurate depth map for identifying occluded pixels.The prediction of the disparity map by semi-global block matching has used the benchmark dataset of Middlebury stereo for evaluation.The improved depth map quality within a reasonable process-ing time outperforms the other existing depth map prediction algorithms.The experimental results have shown that the proposed depth map predictioncould identify the inter-object boundaryeven with the presence ofocclusion with less detection error and runtime.We observed that the Middlebury stereo dataset has very few images with occluded objects,which made the attainment of gain cumbersome.Considering this gain,we have created our dataset with occlu-sion using the structured lighting technique.The proposed regularization term as an optimization process in the graph cut algorithm handles occlusion for different smoothing coefficients.The experimented results demonstrated that our dataset had outperformed the Tsukuba dataset regarding the percentage of occluded pixels.展开更多
In the paper, an approach is proposed for the problem of consistency in depth maps estimation from binocular stereo video sequence. The consistent method includes temporal consistency and spatial consistency to elimin...In the paper, an approach is proposed for the problem of consistency in depth maps estimation from binocular stereo video sequence. The consistent method includes temporal consistency and spatial consistency to eliminate the flickering artifacts and smooth inaccuracy in depth recovery. So the improved global stereo matching based on graph cut and energy optimization is implemented. In temporal domain, the penalty function with coherence factor is introduced for temporal consistency, and the factor is determined by Lucas-Kanade optical flow weighted histogram similarity constraint(LKWHSC). In spatial domain, the joint bilateral truncated absolute difference(JBTAD) is proposed for segmentation smoothing. The method can smooth naturally and uniformly in low-gradient region and avoid over-smoothing as well as keep edge sharpness in high-gradient discontinuities to realize spatial consistency. The experimental results show that the algorithm can obtain better spatial and temporal consistent depth maps compared with the existing algorithms.展开更多
自监督单目深度估计受到了国内外研究人员的广泛关注。现有基于深度学习的自监督单目深度估计方法主要采用编码器-解码器结构。然而,这些方法在编码过程中对输入图像进行下采样操作,导致部分图像信息,尤其是图像的边界信息丢失,进而影...自监督单目深度估计受到了国内外研究人员的广泛关注。现有基于深度学习的自监督单目深度估计方法主要采用编码器-解码器结构。然而,这些方法在编码过程中对输入图像进行下采样操作,导致部分图像信息,尤其是图像的边界信息丢失,进而影响深度图的精度。针对上述问题,提出一种基于拉普拉斯金字塔的自监督单目深度估计方法(Self-supervised Monocular Depth Estimation Based on the Laplace Pyramid,LpDepth)。此方法的核心思想是:首先,使用拉普拉斯残差图丰富编码特征,以弥补在下采样过程中丢失的特征信息;其次,在下采样过程中使用最大池化层突显和放大特征信息,使编码器在特征提取过程中更容易地提取到训练模型所需要的特征信息;最后,使用残差模块解决过拟合问题,提高解码器对特征的利用效率。在KITTI和Make3D等数据集上对所提方法进行了测试,同时将其与现有经典方法进行了比较。实验结果证明了所提方法的有效性。展开更多
基金Supported by the National Natural Science Foundation of China(61572058)
文摘Depth discontinuity edge affects the visual quality of synthesized images in 3D image warping.However,it suffers from accuracy degradation when up-sampled from low-resolution depth maps,especially at large scaling factors.To preserve the accuracy of depth discontinuity,a novel joint bilateral depth super-resolution with intensity guidance method is proposed.Particularly,the fast local intensity classification is exploited to estimate depth coefficients in joint bilateral up-sampling for depth maps,so as to eliminate depth discontinuity edge misalignment.Additionally,the proposed method is accelerated on graphic processing units(GPUs)to meet the requirement of realtime application.Experiments demonstrate that our method can preserve the accuracy of depth discontinuity edges after super resolution,leveraging the visual quality of synthesized image in 3D image warping.
基金National Natural Science Foundation of China(No.62372100)。
文摘Owing to the constraints of depth sensing technology,images acquired by depth cameras are inevitably mixed with various noises.For depth maps presented in gray values,this research proposes a novel denoising model,termed graph-based transform(GBT)and dual graph Laplacian regularization(DGLR)(DGLR-GBT).This model specifically aims to remove Gaussian white noise by capitalizing on the nonlocal self-similarity(NSS)and the piecewise smoothness properties intrinsic to depth maps.Within the group sparse coding(GSC)framework,a combination of GBT and DGLR is implemented.Firstly,within each group,the graph is constructed by using estimates of the true values of the averaged blocks instead of the observations.Secondly,the graph Laplacian regular terms are constructed based on rows and columns of similar block groups,respectively.Lastly,the solution is obtained effectively by combining the alternating direction multiplication method(ADMM)with the weighted thresholding method within the domain of GBT.
基金supported by the National Natural Science Foundation of China(No.41422403)
文摘Least-squares migration （LSM） is applied to image subsurface structures and lithology by minimizing the objective function of the observed seismic and reverse-time migration residual data of various underground reflectivity models. LSM reduces the migration artifacts, enhances the spatial resolution of the migrated images, and yields a more accurate subsurface reflectivity distribution than that of standard migration. The introduction of regularization constraints effectively improves the stability of the least-squares offset. The commonly used regularization terms are based on the L2-norm, which smooths the migration results, e.g., by smearing the reflectivities, while providing stability. However, in exploration geophysics, reflection structures based on velocity and density are generally observed to be discontinuous in depth, illustrating sparse reflectance. To obtain a sparse migration profile, we propose the super-resolution least-squares Kirchhoff prestack depth migration by solving the L0-norm-constrained optimization problem. Additionally, we introduce a two-stage iterative soft and hard thresholding algorithm to retrieve the super-resolution reflectivity distribution. Further, the proposed algorithm is applied to complex synthetic data. Furthermore, the sensitivity of the proposed algorithm to noise and the dominant frequency of the source wavelet was evaluated. Finally, we conclude that the proposed method improves the spatial resolution and achieves impulse-like reflectivity distribution and can be applied to structural interpretations and complex subsurface imaging.
基金supported financially by the National Natural Science Foundation of China (91325301, 41571212 and 41137224)the Project of "One-Three-Five" Strategic Planning & Frontier Sciences of the Institute of Soil Science, Chinese Academy of Sciences (ISSASIP1622)the National Key Basic Research Special Foundation of China (2012FY112100)
文摘Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil spatial heterogeneity is high.In this study,we proposed an integrated method to select environmental covariates for predictive soil depth mapping.First,candidate variables that may influence the development of soil depth were selected based on pedogenetic knowledge.Second,three conventional methods(Pearson correlation analysis(PsCA),generalized additive models(GAMs),and Random Forest(RF))were used to generate optimal combinations of environmental covariates.Finally,three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental covariate.We tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China.A total of 129 soil sampling sites were collected using a representative sampling strategy,and RF and support vector machine(SVM)models were used to map soil depth.The results showed that compared to the set of environmental covariates selected by the three conventional selection methods,the set of environmental covariates selected by the proposed method achieved higher mapping accuracy.The combination from the proposed method obtained a root mean square error(RMSE)of 11.88 cm,which was 2.25–7.64 cm lower than the other methods,and an R^2 value of 0.76,which was 0.08–0.26 higher than the other methods.The results suggest that our method can be used as an alternative to the conventional methods for soil depth mapping and may also be effective for mapping other soil properties.
基金Supported by the Key Project of National Natural Science Foundation of China(Nos.60832003 and 61172096)major Project of Shanghai Science and Technology Committee(No.10510500500)the Major Innovation Project of Shanghai Municipal Education Commission
文摘The depth information of the scene indicates the distance between the object and the camera,and depth extraction is a key technology in 3D video system.The emergence of Kinect makes the high resolution depth map capturing possible.However,the depth map captured by Kinect can not be directly used due to the existing holes and noises,which needs to be repaired.We propose a texture combined inpainting algorithm in this paper.Firstly,the foreground is segmented combined with the color characteristics of the texture image to repair the foreground of the depth map.Secondly,region growing is used to determine the match region of the hole in the depth map,and to accurately position the match region according to the texture information.Then the match region is weighted to fill the hole.Finally,a Gaussian filter is used to remove the noise in the depth map.Experimental results show that the proposed method can effectively repair the holes existing in the original depth map and get an accurate and smooth depth map,which can be used to render a virtual image with good quality.
基金The study was funded by the National Key Technologies R&D Program of China(2018YFC0114800 and 2017YFC0109900)the Natural Science Foundation of China(NSFC)(61405238)+1 种基金the Natural Science Foundation of Jiangsu Province(BK20141206)the Key Technologies R&D Program of Jiangsu Province(BE2018666).
文摘Structured illumination microscopy(SIM)is a promising super-resolution technique for imaging subcellular structures and dynamics due to its compatibility with most commonly usedffuorescent labeling methods.Structured illumination can be obtained by either laser interference or projection of fringe patterns.Here,we proposed a fringe projector composed of a compact multiwavelength LEDs module and a digital micromirror device(DMD)which can be directly attached to most commercial invertedffuorescent microscopes and update it into a SIM system.The effects of the period and duty cycle of fringe patterns on the modulation depth of the structured lightfield were studied.With the optimized fringe pattern,1:6×resolution improvement could be obtained with high-end oil objectives.Multicolor imaging and dynamics of subcellular organelles in live cells were also demonstrated.Our method provides a low-cost solution for SIM setup to expand its wide range of applications to most research labs in thefield of life science and medicine.
文摘Not many bathymetric maps are available for many lakes and reservoirs in developing countries. Usually the bathymetric mapping requires investment in expensive equipment and fieldwork, both of which are not accessible in these countries. This work demonstrates the ability to develop bathymetric map of Mosul Lake by using a digital elevation model (DEM). The depths model of the lake was designed through the use of three main stages;a coastline extraction, dataset interpolation and a triangular irregular network model. The normalized difference water index (NDWI) was used for automatic delineation of the lake coastline from satellite images. The ordinary kriging interpolation with a stable model was used to interpolate the water depths dataset. Finally a triangulated irregular network (TIN) model was used to visualize the resulting interpolation model. Calculated values of area and volume of a TIN model during 2011 were compared with values of supposed initial operation of the reservoir. The differences of water volume storage between these stages at 321 m water level was about 0.81 × 109 m3, where the lake lost around 10% of storage value. Also the results of depths lake model show that the change in water storage between March and July 2011 was about 3.08 × 109 m3.
基金Supported by National Key R&D Program of China(Grant No.2018YFF01012300)National Natural Science Foundation of China(Grant No.11527801).
文摘In the nondestructive testing and evaluation area,magnetic major hysteresis loop measurement technology are widely applied for ferromagnetic material evaluation.However the characterization ability of major hysteresis loop measurement technology greatly varies as the evaluated target properties.To solve this limitation,magnetic minor hysteresis loops,which reflect the responses of ferromagnetic material magnetization in a systematic way,is recommend.Inspired by plenty of information carried by the minor loops,the sensitivity mapping technique was developed to achieve the highest sensitivity of minor-loop parameters to the nondestructively evaluated targets.In this study,for the first time,the sensitivity mapping technique is used to measure the tensile force in a steel strand and evaluate the effective case depth in induction-hardened steel rods.The method and procedures for the sensitivity mapping technique are given before experimental detection.The obtained experimental results indicate that the linear correlation between the induced voltage(or the magnetic induction intensity)and the tensile force(or effective case depth)exists at most of the locations in the cluster of minor loops.The obtained sensitivity maps can be used to optimize the applied magnetic field(or excitation current)and the analyzed locations at the minor loops for achieving the highest sensitivity.For the purpose of tensile force measurement,it is suggested that the strand should be firstly magnetized to the near-saturation state and then restored to the remanent state.In this way,the highest sensitivity is obtained as about 15.26 mV/kN.As for the induction-hardened steel rods,the highest sensitivity of magnetic induction intensity to the effective case depth occurs under low magnetic field conditions and the absolute value of the highest sensitivity is about 0.1110 T/mm.This indicates that if the highest sensitivity is required in the case depth evaluation,the induction-hardened steel rods are only required to be weakly magnetized.The proposed sensitivity mapping technique shows the good performance in the high-sensitivity evaluation of tensile force and case depth in ferromagnetic materials and its application scope can be extended to other nondestructive detection fields.
基金Supported by the National Natural Science Foundation of China(61405191)
文摘A maximum a posteriori（ MAP） algorithm is proposed to improve the accuracy of super resolution（ SR） reconstruction in traditional methods. The algorithm applies both joints image registration and SR reconstruction in the framework,but separates them in the process of iteratiion. Firstly,we estimate the shifting parameters through two lowresolution（ LR） images and use the parameters to reconstruct initial HR images. Then,we update the shifting parameters using HR images. The aforementioned steps are repeated until the ideal HR images are obtained. The metrics such as PSNR and SSIM are used to fully evaluate the quality of the reconstructed image. Experimental results indicate that the proposed method can enhance image resolution efficiently.
基金Sponsored by the Jiangsu Prospective Joint Research Project(Grant No.BY2016022-28)
文摘Recognition of the human actions by computer vision has become an active research area in recent years. Due to the speed and the high similarity of the actions, the current algorithms cannot get high recognition rate. A new recognition method of the human action is proposed with the multi-scale directed depth motion maps(MsdDMMs) and Log-Gabor filters. According to the difference between the speed and time order of an action, MsdDMMs is proposed under the energy framework. Meanwhile, Log-Gabor is utilized to describe the texture details of MsdDMMs for the motion characteristics. It can easily satisfy both the texture characterization and the visual features of human eye. Furthermore, the collaborative representation is employed as action recognition by the classification. Experimental results show that the proposed algorithm, which is applied in the MSRAction3 D dataset and MSRGesture3 D dataset, can achieve the accuracy of 95.79% and 96.43% respectively. It also has higher accuracy than the existing algorithms, such as super normal vector(SNV), hierarchical recurrent neural network(Hierarchical RNN).
文摘This paper proposes a new technique that is used to embed depth maps into corresponding 2-dimensional （2D） images. Since a 2D image and its depth map are integrated into one type of image format, they can be treated as if they were one 2D image. Thereby, it can reduce the amount of data in 3D images by half and simplify the processes for sending them through networks because the synchronization between images for the left and right eyes becomes unnecessary. We embed depth maps in the quantized discrete cosine transform （DCT） data of 2D images. The key to this technique is whether the depth maps could be embedded into 2D images without perceivably deteriorating their quality. We try to reduce their deterioration by compressing the depth map data by using the differences from the next pixel to the left. We assume that there is only one non-zero pixel at most on one horizontal line in the DCT block because the depth map values change abruptly. We conduct an experiment to evaluate the quality of the 2D images embedded with depth maps and find that satisfactory quality could be achieved.
文摘A new method of super-resolution image reconstruction is proposed,which uses a three-step-training error backpropagation neural network(BPNN)to realize the super-resolution reconstruction(SRR)of satellite image.The method is based on BPNN.First,three groups learning samples with different resolutions are obtained according to image observation model,and then vector mappings are respectively used to those three group learning samples to speed up the convergence of BPNN,at last,three times consecutive training are carried on the BPNN.Training samples used in each step are of higher resolution than those used in the previous steps,so the increasing weights store a great amount of information for SRR,and network performance and generalization ability are improved greatly.Simulation and generalization tests are carried on the well-trained three-step-training NN respectively,and the reconstruction results with higher resolution images verify the effectiveness and validity of this method.
文摘Generation of a depth-map from 2D video is the kernel of DIBR (Depth Image Based Rendering) in 2D-3D video conversion systems. However it occupies over most of the system resource where the motion search module takes up 90% time-consuming in typical motion estimation-based depth-map generation algorithms. In order to reduce the computational complexity, in this paper a new fast depth-map generation algorithm based on motion search is developed, in which a fast diamond search algorithm is adopted to decide whether a 16x16 or 4x4 block size is used based on Sobel operator in the motion search module to obtain a sub-depth-map. Then the sub-depth-map will be fused with the sub-depth-maps gotten from depth from color component Cr and depth from linear perspective modules to compensate and refine detail of the depth-map, finally obtain a better depth-map. The simulation results demonstrate that the new approach can greatly reduce over 50% computational complexity compared to other existing methods.
基金supported by the National Natural Science Foundation of China(Grant No.60832003)Key Laboratory of Advanced Display and System Application(Shanghai University),Ministry of Education,China(Grant No.P200902)the Key Project of Science and Technology Commission of Shanghai Municipality(Grant No.10510500500)
文摘Depth maps are used for synthesis virtual view in free-viewpoint television （FTV） systems. When depth maps are derived using existing depth estimation methods, the depth distortions will cause undesirable artifacts in the synthesized views. To solve this problem, a 3D video quality model base depth maps （D-3DV） for virtual view synthesis and depth map coding in the FTV applications is proposed. First, the relationships between distortions in coded depth map and rendered view are derived. Then, a precisely 3DV quality model based depth characteristics is develop for the synthesized virtual views. Finally, based on D-3DV model, a multilateral filtering is applied as a pre-processed filter to reduce rendering artifacts. The experimental results evaluated by objective and subjective methods indicate that the proposed D-3DV model can reduce bit-rate of depth coding and achieve better rendering quality.
文摘The creation of the 3D rendering model involves the prediction of an accurate depth map for the input images.A proposed approach of a modified semi-global block matching algorithm with variable window size and the gradient assessment of objects predicts the depth map.3D modeling and view synthesis algorithms could effectively handle the obtained disparity maps.This work uses the consistency check method to find an accurate depth map for identifying occluded pixels.The prediction of the disparity map by semi-global block matching has used the benchmark dataset of Middlebury stereo for evaluation.The improved depth map quality within a reasonable process-ing time outperforms the other existing depth map prediction algorithms.The experimental results have shown that the proposed depth map predictioncould identify the inter-object boundaryeven with the presence ofocclusion with less detection error and runtime.We observed that the Middlebury stereo dataset has very few images with occluded objects,which made the attainment of gain cumbersome.Considering this gain,we have created our dataset with occlu-sion using the structured lighting technique.The proposed regularization term as an optimization process in the graph cut algorithm handles occlusion for different smoothing coefficients.The experimented results demonstrated that our dataset had outperformed the Tsukuba dataset regarding the percentage of occluded pixels.
基金the Science and Technology Innovation Project of Ministry of Culture of China(No.2014KJCXXM08)the National Key Technology Research and Development Program of the Ministry of Science and Technology of China(No.2012BAH37F02)the National High Technology Research and Development Program(863)of China(No.2011AA01A107)
文摘In the paper, an approach is proposed for the problem of consistency in depth maps estimation from binocular stereo video sequence. The consistent method includes temporal consistency and spatial consistency to eliminate the flickering artifacts and smooth inaccuracy in depth recovery. So the improved global stereo matching based on graph cut and energy optimization is implemented. In temporal domain, the penalty function with coherence factor is introduced for temporal consistency, and the factor is determined by Lucas-Kanade optical flow weighted histogram similarity constraint(LKWHSC). In spatial domain, the joint bilateral truncated absolute difference(JBTAD) is proposed for segmentation smoothing. The method can smooth naturally and uniformly in low-gradient region and avoid over-smoothing as well as keep edge sharpness in high-gradient discontinuities to realize spatial consistency. The experimental results show that the algorithm can obtain better spatial and temporal consistent depth maps compared with the existing algorithms.
文摘自监督单目深度估计受到了国内外研究人员的广泛关注。现有基于深度学习的自监督单目深度估计方法主要采用编码器-解码器结构。然而,这些方法在编码过程中对输入图像进行下采样操作,导致部分图像信息,尤其是图像的边界信息丢失,进而影响深度图的精度。针对上述问题,提出一种基于拉普拉斯金字塔的自监督单目深度估计方法(Self-supervised Monocular Depth Estimation Based on the Laplace Pyramid,LpDepth)。此方法的核心思想是:首先,使用拉普拉斯残差图丰富编码特征,以弥补在下采样过程中丢失的特征信息;其次,在下采样过程中使用最大池化层突显和放大特征信息,使编码器在特征提取过程中更容易地提取到训练模型所需要的特征信息;最后,使用残差模块解决过拟合问题,提高解码器对特征的利用效率。在KITTI和Make3D等数据集上对所提方法进行了测试,同时将其与现有经典方法进行了比较。实验结果证明了所提方法的有效性。
