The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resoluti...The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resolution remote sensing images,we present an effective YOLOv3 framework,corner regression-based YOLOv3(Correg-YOLOv3),to localize dense building accurately.This improved YOLOv3 algorithm establishes a vertex regression mechanism and an additional loss item about building vertex offsets relative to the center point of bounding box.By extending output dimensions,the trained model is able to output the rectangular bounding boxes and the building vertices meanwhile.Finally,we evaluate the performance of the Correg-YOLOv3 on our self-produced data set and provide a comparative analysis qualitatively and quantitatively.The experimental results achieve high performance in precision(96.45%),recall rate(95.75%),F1 score(96.10%)and average precision(98.05%),which were 2.73%,5.4%,4.1%and 4.73%higher than that of YOLOv3.Therefore,our proposed algorithm effectively tackles the problem of dense building detection in high resolution images.展开更多
Road extraction plays an important role in many applications such as car navigation, but the manual extraction of roads is a laborious, tedious task. To speed the extraction of roads, an approach based on particle fil...Road extraction plays an important role in many applications such as car navigation, but the manual extraction of roads is a laborious, tedious task. To speed the extraction of roads, an approach based on particle filtering to extract automatically roads from high resolution imagery is proposed. Particle filtering provides a statistical framework for propagating sample-based approximations of posterior distributions and has almost no restriction on the ingredients of the model. We integrate the similarity of grey value and the edge point distribution of roads into particle filtering to deal with complex scenes. To handle road appearance changes the tracking algorithm is allowed to update the road model during temporally stable image observations. A fully automatic initialization strategy is used. Experimental results show that the proposed approach is a promising and fully automatic method for extracting roads from images, even in the presence of occlusions.展开更多
Small-object detection has long been a challenge.High-megapixel cameras are used to solve this problem in industries.However,current detectors are inefficient for high-resolution images.In this work,we propose a new m...Small-object detection has long been a challenge.High-megapixel cameras are used to solve this problem in industries.However,current detectors are inefficient for high-resolution images.In this work,we propose a new module called Pre-Locate Net,which is a plug-and-play structure that can be combined with most popular detectors.We inspire the use of classification ideas to obtain candidate regions in images,greatly reducing the amount of calculation,and thus achieving rapid detection in high-resolution images.Pre-Locate Net mainly includes two parts,candidate region classification and behavior classification.Candidate region classification is used to obtain a candidate region,and behavior classification is used to estimate the scale of an object.Different follow-up processing is adopted according to different scales to balance the variance of the network input.Different from the popular candidate region generation method,we abandon the idea of regression of a bounding box and adopt the concept of classification,so as to realize the prediction of a candidate region in the shallow network.We build a high-resolution dataset of aircraft and landing gears covering complex scenes to verify the effectiveness of our method.Compared to state-of-the-art detectors(e.g.,Guided Anchoring,Libra-RCNN,and FASF),our method achieves the best m AP of 94.5 on 1920×1080 images at 16.7 FPS.展开更多
Accurate information on the location and magnitude of vegetation change in scenic areas can guide the configuration of tourism facilities and the formulation of vegetation protection measures.High spatial resolution r...Accurate information on the location and magnitude of vegetation change in scenic areas can guide the configuration of tourism facilities and the formulation of vegetation protection measures.High spatial resolution remote sensing images can be used to detect subtle vegetation changes.The major objective of this study was to map and quantify forest vegetation changes in a national scenic location,the Purple Mountains of Nanjing,China,using multi-temporal cross-sensor high spatial resolution satellite images to identify the main drivers of the vegetation changes and provide a reference for sustainable management.We used Quickbird images acquired in 2004,IKONOS images acquired in 2009,and WorldView2 images acquired in 2015.Four pixel-based direct change detection methods including the normalized difference vegetation index difference method,multi-index integrated change analysis(MIICA),principal component analysis,and spectral gradient difference analysis were compared in terms of their change detection performances.Subsequently,the best pixel-based detection method in conjunction with object-oriented image analysis was used to extract subtle forest vegetation changes.An accuracy assessment using the stratified random sampling points was conducted to evaluate the performance of the change detection results.The results showed that the MIICA method was the best pixel-based change detection method.And the object-oriented MIICA with an overall accuracy of 0.907 and a kappa coefficient of 0.846 was superior to the pixel-based MIICA.From 2004 to 2009,areas of vegetation gain mainly occurred around the periphery of the study area,while areas of vegetation loss were observed in the interior and along the boundary of the study area due to construction activities,which contributed to 79%of the total area of vegetation loss.During 2009–2015,the greening initiatives around the construction areas increased the forest vegetation coverage,accounting for 84%of the total area of vegetation gain.In spite of this,vegetation loss occurred in the interior of the Purple Mountains due to infrastructure development that caused conversion from vegetation to impervious areas.We recommend that:(1)a local multi-agency team inspect and assess law enforcement regarding natural resource utilization;and(2)strengthen environmental awareness education.展开更多
[ Objective] The study aimed to improve methods of monitoring Karst Rocky Desertification （KRD） control projects and increase the working efficiency. [Method] Based on remote sensing images with medium and high spat...[ Objective] The study aimed to improve methods of monitoring Karst Rocky Desertification （KRD） control projects and increase the working efficiency. [Method] Based on remote sensing images with medium and high spatial resolution, KRD control projects in Disi River basin in Puan County were monitored, that is, information of the project construction in the study area was extracted using supervised classification and hu- man-computer interactive interpretation, and the monitoring results were testified with the aid of GPS. [Result] It was feasible to monitor KRD con- trol projects in Disi River basin based on remote sensing images with medium and high resolution, and the monitoring accuracy was satisfactory, reaching above 80% or 90%, so the method is worthy of popularizing. [ Conclusion] Remote sensing images with medium and high resolution can be used to monitor other KRD control Droiects.展开更多
Calman filtering method based on wavelet transform has been successfully applied to signal denoising. According to the different application methods and the realization forms of Calman filter, combined with the struct...Calman filtering method based on wavelet transform has been successfully applied to signal denoising. According to the different application methods and the realization forms of Calman filter, combined with the structural analysis of wavelet decomposition, we present kinds of multi-scale filtering methods into the category of the three. The simulation results show that the multi-scale Calman filtering method based on system layer has better performance. Synthetic aperture radar （SAR） images have rich texture information, which can reflect the spatial structure of objects. The texture feature is widely used in SAR image classification and SAR image segmentation. Affected by imaging factors, the direct use of texture features extracted from SAR images is not good enough. In order to avoid the traditional method of filtering followed the texture feature extraction caused by the loss of texture and edge information, this paper presents a texture feature extraction of SAR image, then using Robust PCA method, finally using texture feature clustering method K-means test after treatment with RPCA expression.展开更多
Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilizatio...Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilization). However, in some mobile devices applications (e.g. image sequence panoramic stitching), the high resolution is necessary to obtain satisfactory quality of panoramic image. However, the computational cost will become too expensive to be suitable for the low power consumption requirement of mobile device. The full search algorithm can obtain the global minimum with extremely computational cost, while the typical fast algorithms may suffer from the local minimum problem. This paper proposed a fast algorithm to deal with 2560 × 1920 high-resolution (HR) image sequences. The proposed method estimates the motion vector by a two-level coarse-to-fine scheme which only exploits sparse reference blocks (25 blocks in this paper) in each level to determine the global motion vector, thus the computational costs are significantly decreased. In order to increase the effective search range and robustness, the predictive motion vector (PMV) technique is used in this work. By the comparisons of computational complexity, the proposed algorithm costs less addition operations than the typical Three-Step Search algorithm (TSS) for estimating the global motion of the HR images without the local minimum problem. The quantitative evaluations show that our method is comparable to the full search algorithm (FSA) which is considered to be the golden baseline.展开更多
In many cases,the Digital Surface Models(DSMs)and Digital Elevation Models(DEMs)are obtained with Light Detection and Ranging(LiDAR)or stereo matching.As an active method,LiDAR is very accurate but expensive,thus ofte...In many cases,the Digital Surface Models(DSMs)and Digital Elevation Models(DEMs)are obtained with Light Detection and Ranging(LiDAR)or stereo matching.As an active method,LiDAR is very accurate but expensive,thus often limiting its use in small-scale acquisition.Stereo matching is suitable for large-scale acquisition of terrain information as the increase of satellite stereo sensors.However,underperformance of stereo matching easily occurs in textureless areas.Accordingly,this study proposed a Shading Aware DSM GEneration Method(SADGE)with high resolution multi-view satellite images.Considering the complementarity of stereo matching and Shape from Shading(SfS),SADGE combines the advantage of stereo matching and SfS technique.First,an improved Semi-Global Matching(SGM)technique is used to generate an initial surface expressed by a DSM;then,it is refined by optimizing the objective function which modeled the imaging process with the illumination,surface albedo,and normal object surface.Different from the existing shading-based DEM refinement or generation method,no information about the illumination or the viewing angle is needed while concave/convex ambiguity can be avoided as multi-view images are utilized.Experiments with ZiYuan-3 and GaoFen-7 images show that the proposed method can generate higher accuracy DSM(12.5-56.3%improvement)with sound overall shape and temporarily detailed surface compared with a software solution(SURE)for multi-view stereo.展开更多
The dispersoid phase Al_(20)Cu_2Mn_3 in a 2024 Al alloy is commonly composed of twins,An ob- servation of corresponding high resolution image shows that the twin boundary plane is a glide plane other than mirror one.T...The dispersoid phase Al_(20)Cu_2Mn_3 in a 2024 Al alloy is commonly composed of twins,An ob- servation of corresponding high resolution image shows that the twin boundary plane is a glide plane other than mirror one.Two neighbouring components of twins are not symmetry of re- flection or rotation,but of glide reflection.The“diamond”glide plane is(101)and the glide vector is(1/4)(-).Components of twins in the phase take shape of prism with the longitudinal edge being parallel to[010]and side faces being{101}and{100}.展开更多
BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and H...BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and HFS caused by NVC. The judgement of NVC is a critical step in the preoperative evaluation of MVD, which is related to the effect of MVD treatment. Magnetic resonance imaging(MRI) technology has been used to detect NVC prior to MVD for several years. Among many MRI sequences, three-dimensional time-of-flight magnetic resonance angiography(3D TOF MRA) is the most widely used. However, 3D TOF MRA has some shortcomings in detecting NVC. Therefore, 3D TOF MRA combined with high resolution T2-weighted imaging(HR T2WI) is considered to be a more effective method to detect NVC.AIM To determine the value of 3D TOF MRA combined with HR T2WI in the judgment of NVC, and thus to assess its value in the preoperative evaluation of MVD.METHODS Related studies published from inception to September 2022 based on PubMed, Embase, Web of Science, and the Cochrane Library were retrieved. Studies that investigated 3D TOF MRA combined with HR T2WI to judge NVC in patients with TN or HFS were included according to the inclusion criteria. Studies without complete data or not relevant to the research topics were excluded. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to assess the quality of included studies. The publication bias of the included literature was examined by Deeks’ test. An exact binomial rendition of the bivariate mixed-effects regression model was used to synthesize data. Data analysis was performed using the MIDAS module of statistical software Stata 16.0. Two independent investigators extracted patient and study characteristics, and discrepancies were resolved by consensus. Individual and pooled sensitivities and specificities were calculated. The I_(2) statistic and Q test were used to test heterogeneity. The study was registered on the website of PROSERO(registration No. CRD42022357158).RESULTS Our search identified 595 articles, of which 12(including 855 patients) fulfilled the inclusion criteria. Bivariate analysis showed that the pooled sensitivity and specificity of 3D TOF MRA combined with HR T2WI for detecting NVC were 0.96 [95% confidence interval(CI): 0.92-0.98] and 0.92(95%CI: 0.74-0.98), respectively. The pooled positive likelihood ratio was 12.4(95%CI: 3.2-47.8), pooled negative likelihood ratio was 0.04(95%CI: 0.02-0.09), and pooled diagnostic odds ratio was 283(95%CI: 50-1620). The area under the receiver operating characteristic curve was 0.98(95%CI: 0.97-0.99). The studies showed no substantial heterogeneity(I2 = 0, Q = 0.001 P = 0.50).CONCLUSION Our results suggest that 3D TOF MRA combined with HR T2WI has excellent sensitivity and specificity for judging NVC in patients with TN or HFS. This method can be used as an effective tool for preoperative evaluation of MVD.展开更多
In the process of image transmission, the famous JPEG and JPEG-2000 compression methods need more transmission time as it is difficult for them to compress the image with a low compression rate. Recently the compresse...In the process of image transmission, the famous JPEG and JPEG-2000 compression methods need more transmission time as it is difficult for them to compress the image with a low compression rate. Recently the compressed sensing（CS） theory was proposed, which has earned great concern as it can compress an image with a low compression rate, meanwhile the original image can be perfectly reconstructed from only a few compressed data. The CS theory is used to transmit the high resolution astronomical image and build the simulation environment where there is communication between the satellite and the Earth. Number experimental results show that the CS theory can effectively reduce the image transmission and reconstruction time. Even with a very low compression rate, it still can recover a higher quality astronomical image than JPEG and JPEG-2000 compression methods.展开更多
Single-pixel imaging(SPI)through complex media remains challenging.In this paper,we report high-resolution common-path SPI with dual polarization using random-frequency-encoded time sequences in complex environments w...Single-pixel imaging(SPI)through complex media remains challenging.In this paper,we report high-resolution common-path SPI with dual polarization using random-frequency-encoded time sequences in complex environments where the illumination and detection paths are severely distorted.By leveraging a common-path optical configuration with orthogonal polarization states,a series of dynamic scaling factors can be corrected.The designed random-frequency encoding scheme disperses scattering-induced noise into artifacts to be simply removed.It is demonstrated in optical experiments that the proposed method is feasible and effective to reconstruct highresolution object images in complex environments.The proposed method does not require complex optical components and prior knowledge about scattering media,providing a robust solution for high-resolution optical imaging in complex scenarios where the illumination and detection paths are severely distorted at the same time.展开更多
Achieving clear and deep tissue imaging with optical coherence tomography(OCT)necessitates the simultaneous optimization of three critical factors:high resolution,extended depth of focus(DOF),and high signal-tonoise r...Achieving clear and deep tissue imaging with optical coherence tomography(OCT)necessitates the simultaneous optimization of three critical factors:high resolution,extended depth of focus(DOF),and high signal-tonoise ratio(SNR).Conventional OCT systems often compromise one or more of these factors,due to inherent trade-offs in optical design and noise management.To address these limitations,we present a chromatic OCT system that simultaneously optimizes all three parameters.The system achieves an isotropic spatial resolution of 2 to 3μm by leveraging a broad bandwidth light source and high-numerical-aperture optics with a pronounced chromatic focal shift,which enables up to a sevenfold DOF extension.Additionally,a novel noise-gating algorithm suppresses system-inherent noise,sidelobe artifacts,and multiple scattering effects,significantly enhancing the SNR.Comparative simulations and experiments demonstrate that the proposed chromatic OCT outperforms conventional high-resolution systems by maintaining superior resolution and SNR over an extended imaging range.These advancements establish chromatic OCT as a powerful tool for high-resolution,deep tissue imaging in biomedical applications,offering improved diagnostic capabilities.展开更多
Background：There are few studies for evaluating wall characteristics of intracranial vertebral artery hypoplasia （VAH）.The aim of this study was to determine wall characteristics of VAH with three-dimensional volum...Background：There are few studies for evaluating wall characteristics of intracranial vertebral artery hypoplasia （VAH）.The aim of this study was to determine wall characteristics of VAH with three-dimensional volumetric isotropic turbo spin echo acquisition （3D VISTA） images and differentiate between acquired atherosclerotic stenosis and VAH.Methods：Thirty patients with suspicious VAH by luminograms were retrospectively enrolled between January 2014 and February 2015.The patients were classified as ＂acquired atherosclerotic stenosis＂ or ＂VAH＂ based on 3D VISTA images.The wall characteristics of VAH were assessed to determine the presence of atherosclerotic lesions,and the patients were classified into two subgroups （VAH with atherosclerosis and VAH with normal wall）.Wall characteristics of basilar arteries and vertebral arteries were also assessed.The clinical and wall characteristics were compared between the two groups.Results：Five of 30 patients with suspicious VAH were finally diagnosed as acquired atherosclerotic stenosis by 3D VISTA images.25 patients were finally diagnosed as VAH including 16 （64.00%） patients with atherosclerosis and 9 （36.00%） patients with normal wall.In the 16 patients with atherosclerosis,plaque was found in 9 patients,slight wall thickening in 6 patients,and thrombus and wall thickening in 1 patient.Compared with VAH patients with normal wall,VAH patients with atherosclerosis showed atherosclerotic basilar arteries and dominant vertebral arteries more frequently （P =0.000）.Conclusions：Three-dimensional VISTA images enable differentiation between the acquired atherosclerotic stenosis and VAH.VAH was also prone to atherosclerotic processes.展开更多
Spectral imaging—a suite of techniques combining image acquisition with extremely high color resolution—plays an ever-increasing role in many fields,such as biomedicine,agriculture,geology,archeology,and environment...Spectral imaging—a suite of techniques combining image acquisition with extremely high color resolution—plays an ever-increasing role in many fields,such as biomedicine,agriculture,geology,archeology,and environmental control.^(1-3)The capability of visualizing,in real time,a tissue or terrain with spatially resolved chemical sensitivity can literally mean the difference between life and death.To appreciate the significance,consider how in vivo spectroscopic sensing of malignant tissue empowers the surgeon to minimize collateral damage during tumor removal while keeping the risk of cancer recurrence low.展开更多
Fourier series analysis is proposed as a new technique to address the problem of“sub-pixel motion”in deriving cloud motion winds(CMW)from high temporal resolution images.Based on a concept different from that of max...Fourier series analysis is proposed as a new technique to address the problem of“sub-pixel motion”in deriving cloud motion winds(CMW)from high temporal resolution images.Based on a concept different from that of maximum correlation matching technique,the Fourier technique computes phase speed as an estimate of cloud motion.It is very effective for tracking small cellular clouds in 1-min interval images and more efficient for computation than the maximum correlation technique because only two templates in same size are involved in primary tracking procedure. Moreover it obtains not only CMW vectors but potentially also velocity spectrum and variance.A practical example is given to show the cloud motion winds from 1-min interval images with the Fourier method versus those from traditional 30-min interval images with maximum correlation technique.Problems that require further investigation before the Fourier technique can be regarded as a viable technique,especially for cloud tracking with high temporal resolution images,are also revealed.展开更多
While impressive direct geolocation accuracies better than 5.0 m CE90(90%of circular error)can be achieved from the last DigitalGlobe’s Very High Resolution(VHR)satellites(i.e.GeoEye-1 and WorldView-1/2/3/4),it is in...While impressive direct geolocation accuracies better than 5.0 m CE90(90%of circular error)can be achieved from the last DigitalGlobe’s Very High Resolution(VHR)satellites(i.e.GeoEye-1 and WorldView-1/2/3/4),it is insufficient for many precise geodetic applications.For these sensors,the best horizontal geopositioning accuracies(around 0.55 m CE90)can be attained by using third-order 3D rational functions with vendor’s rational polynomial coefficients data refined by a zero-order polynomial adjustment obtained from a small number of very accurate ground control points(GCPs).However,these high-quality GCPs are not always available.In this work,two different approaches for improving the initial direct geolocation accuracy of VHR satellite imagery are proposed.Both of them are based on the extraction of three-dimensional GCPs from freely available ancillary data at global coverage such as multi-temporal information of Google Earth and the Shuttle Radar Topography Mission 30 m digital elevation model.The application of these approaches on WorldView-2 and GeoEye-1 stereo pairs over two different study sites proved to improve the horizontal direct geolocation accuracy values around of 75%.展开更多
Mesoscopy refers to imaging methodologies that provide a field of view(FOV)ranging from several millimeters to centimeters while achieving cellular or even subcellular resolution(Figure 1).This technological framework...Mesoscopy refers to imaging methodologies that provide a field of view(FOV)ranging from several millimeters to centimeters while achieving cellular or even subcellular resolution(Figure 1).This technological framework employs specially designed large-scale objective lenses to correct aberrations across extended FOVs,synchronized with light-field acquisition modalities through either scanning point detection or large-format array detection.Conventional microscopes,constrained by the limitations of objective lenses,exhibit a trade-off between the FOV and resolution.To achieve both high resolution and a large FOV,common approaches such as FOV stitching and Fourier ptychography were employed.However,these methods were extremely slow and imposed numerous constraints on samples.In 2016,a mesoscopic objective lens was introduced to address these challenges,achieving a 6 mm FOV and 0.7 mm resolution,thereby increasing the imaging throughput of conventional objective lenses by orders of magnitude.1 In the same year,this technology was recognized as one of the top ten physics breakthroughs worldwide by Physics World.Since then,mesoscopic imaging technology has gradually gained momentum and has been applied in various fields.展开更多
In the field of optoelectronics,certain types of data may be difficult to accurately annotate,such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges.Weakly supervised learning can...In the field of optoelectronics,certain types of data may be difficult to accurately annotate,such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges.Weakly supervised learning can provide a more reliable approach in these situations.Current popular approaches mainly adopt the classification-based class activation maps(CAM)as initial pseudo labels to solve the task.展开更多
Introduction of the stepwise phase dispersion compensation layer allowed broadband achromatic metalens to have a high numerical aperture,which enabled high-resolution metalens imaging.
基金National Natural Science Foundation of China(No.41871305)National Key Research and Development Program of China(No.2017YFC0602204)+2 种基金Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)(No.CUGQY1945)Open Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education and the Fundamental Research Funds for the Central Universities(No.GLAB2019ZR02)Open Fund of Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources,China(No.KF-2020-05-068)。
文摘The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resolution remote sensing images,we present an effective YOLOv3 framework,corner regression-based YOLOv3(Correg-YOLOv3),to localize dense building accurately.This improved YOLOv3 algorithm establishes a vertex regression mechanism and an additional loss item about building vertex offsets relative to the center point of bounding box.By extending output dimensions,the trained model is able to output the rectangular bounding boxes and the building vertices meanwhile.Finally,we evaluate the performance of the Correg-YOLOv3 on our self-produced data set and provide a comparative analysis qualitatively and quantitatively.The experimental results achieve high performance in precision(96.45%),recall rate(95.75%),F1 score(96.10%)and average precision(98.05%),which were 2.73%,5.4%,4.1%and 4.73%higher than that of YOLOv3.Therefore,our proposed algorithm effectively tackles the problem of dense building detection in high resolution images.
文摘Road extraction plays an important role in many applications such as car navigation, but the manual extraction of roads is a laborious, tedious task. To speed the extraction of roads, an approach based on particle filtering to extract automatically roads from high resolution imagery is proposed. Particle filtering provides a statistical framework for propagating sample-based approximations of posterior distributions and has almost no restriction on the ingredients of the model. We integrate the similarity of grey value and the edge point distribution of roads into particle filtering to deal with complex scenes. To handle road appearance changes the tracking algorithm is allowed to update the road model during temporally stable image observations. A fully automatic initialization strategy is used. Experimental results show that the proposed approach is a promising and fully automatic method for extracting roads from images, even in the presence of occlusions.
基金the National Science Fund for Distinguished Young Scholars of China (No. 51625501)the Aeronautical Science Foundation of China (No. 201946051002)
文摘Small-object detection has long been a challenge.High-megapixel cameras are used to solve this problem in industries.However,current detectors are inefficient for high-resolution images.In this work,we propose a new module called Pre-Locate Net,which is a plug-and-play structure that can be combined with most popular detectors.We inspire the use of classification ideas to obtain candidate regions in images,greatly reducing the amount of calculation,and thus achieving rapid detection in high-resolution images.Pre-Locate Net mainly includes two parts,candidate region classification and behavior classification.Candidate region classification is used to obtain a candidate region,and behavior classification is used to estimate the scale of an object.Different follow-up processing is adopted according to different scales to balance the variance of the network input.Different from the popular candidate region generation method,we abandon the idea of regression of a bounding box and adopt the concept of classification,so as to realize the prediction of a candidate region in the shallow network.We build a high-resolution dataset of aircraft and landing gears covering complex scenes to verify the effectiveness of our method.Compared to state-of-the-art detectors(e.g.,Guided Anchoring,Libra-RCNN,and FASF),our method achieves the best m AP of 94.5 on 1920×1080 images at 16.7 FPS.
基金supported by the National Natural Science Foundation of China(31670552)the PAPD(Priority Academic Program Development)of Jiangsu provincial universities and the China Postdoctoral Science Foundation funded projectthis work was performed while the corresponding author acted as an awardee of the 2017 Qinglan Project sponsored by Jiangsu Province。
文摘Accurate information on the location and magnitude of vegetation change in scenic areas can guide the configuration of tourism facilities and the formulation of vegetation protection measures.High spatial resolution remote sensing images can be used to detect subtle vegetation changes.The major objective of this study was to map and quantify forest vegetation changes in a national scenic location,the Purple Mountains of Nanjing,China,using multi-temporal cross-sensor high spatial resolution satellite images to identify the main drivers of the vegetation changes and provide a reference for sustainable management.We used Quickbird images acquired in 2004,IKONOS images acquired in 2009,and WorldView2 images acquired in 2015.Four pixel-based direct change detection methods including the normalized difference vegetation index difference method,multi-index integrated change analysis(MIICA),principal component analysis,and spectral gradient difference analysis were compared in terms of their change detection performances.Subsequently,the best pixel-based detection method in conjunction with object-oriented image analysis was used to extract subtle forest vegetation changes.An accuracy assessment using the stratified random sampling points was conducted to evaluate the performance of the change detection results.The results showed that the MIICA method was the best pixel-based change detection method.And the object-oriented MIICA with an overall accuracy of 0.907 and a kappa coefficient of 0.846 was superior to the pixel-based MIICA.From 2004 to 2009,areas of vegetation gain mainly occurred around the periphery of the study area,while areas of vegetation loss were observed in the interior and along the boundary of the study area due to construction activities,which contributed to 79%of the total area of vegetation loss.During 2009–2015,the greening initiatives around the construction areas increased the forest vegetation coverage,accounting for 84%of the total area of vegetation gain.In spite of this,vegetation loss occurred in the interior of the Purple Mountains due to infrastructure development that caused conversion from vegetation to impervious areas.We recommend that:(1)a local multi-agency team inspect and assess law enforcement regarding natural resource utilization;and(2)strengthen environmental awareness education.
基金Supported by the Key Science and Technology Projects of Guizhou Province,China[(2007)3017,(2008)3022]Major Special Project of Guizhou Province,China(2006-6006-2)
文摘[ Objective] The study aimed to improve methods of monitoring Karst Rocky Desertification （KRD） control projects and increase the working efficiency. [Method] Based on remote sensing images with medium and high spatial resolution, KRD control projects in Disi River basin in Puan County were monitored, that is, information of the project construction in the study area was extracted using supervised classification and hu- man-computer interactive interpretation, and the monitoring results were testified with the aid of GPS. [Result] It was feasible to monitor KRD con- trol projects in Disi River basin based on remote sensing images with medium and high resolution, and the monitoring accuracy was satisfactory, reaching above 80% or 90%, so the method is worthy of popularizing. [ Conclusion] Remote sensing images with medium and high resolution can be used to monitor other KRD control Droiects.
文摘Calman filtering method based on wavelet transform has been successfully applied to signal denoising. According to the different application methods and the realization forms of Calman filter, combined with the structural analysis of wavelet decomposition, we present kinds of multi-scale filtering methods into the category of the three. The simulation results show that the multi-scale Calman filtering method based on system layer has better performance. Synthetic aperture radar （SAR） images have rich texture information, which can reflect the spatial structure of objects. The texture feature is widely used in SAR image classification and SAR image segmentation. Affected by imaging factors, the direct use of texture features extracted from SAR images is not good enough. In order to avoid the traditional method of filtering followed the texture feature extraction caused by the loss of texture and edge information, this paper presents a texture feature extraction of SAR image, then using Robust PCA method, finally using texture feature clustering method K-means test after treatment with RPCA expression.
文摘Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilization). However, in some mobile devices applications (e.g. image sequence panoramic stitching), the high resolution is necessary to obtain satisfactory quality of panoramic image. However, the computational cost will become too expensive to be suitable for the low power consumption requirement of mobile device. The full search algorithm can obtain the global minimum with extremely computational cost, while the typical fast algorithms may suffer from the local minimum problem. This paper proposed a fast algorithm to deal with 2560 × 1920 high-resolution (HR) image sequences. The proposed method estimates the motion vector by a two-level coarse-to-fine scheme which only exploits sparse reference blocks (25 blocks in this paper) in each level to determine the global motion vector, thus the computational costs are significantly decreased. In order to increase the effective search range and robustness, the predictive motion vector (PMV) technique is used in this work. By the comparisons of computational complexity, the proposed algorithm costs less addition operations than the typical Three-Step Search algorithm (TSS) for estimating the global motion of the HR images without the local minimum problem. The quantitative evaluations show that our method is comparable to the full search algorithm (FSA) which is considered to be the golden baseline.
基金supported by the National Natural Science Foundation of China[grant number 41801390]the National Key R&D Program of China[grant number 2018YFD1100405].
文摘In many cases,the Digital Surface Models(DSMs)and Digital Elevation Models(DEMs)are obtained with Light Detection and Ranging(LiDAR)or stereo matching.As an active method,LiDAR is very accurate but expensive,thus often limiting its use in small-scale acquisition.Stereo matching is suitable for large-scale acquisition of terrain information as the increase of satellite stereo sensors.However,underperformance of stereo matching easily occurs in textureless areas.Accordingly,this study proposed a Shading Aware DSM GEneration Method(SADGE)with high resolution multi-view satellite images.Considering the complementarity of stereo matching and Shape from Shading(SfS),SADGE combines the advantage of stereo matching and SfS technique.First,an improved Semi-Global Matching(SGM)technique is used to generate an initial surface expressed by a DSM;then,it is refined by optimizing the objective function which modeled the imaging process with the illumination,surface albedo,and normal object surface.Different from the existing shading-based DEM refinement or generation method,no information about the illumination or the viewing angle is needed while concave/convex ambiguity can be avoided as multi-view images are utilized.Experiments with ZiYuan-3 and GaoFen-7 images show that the proposed method can generate higher accuracy DSM(12.5-56.3%improvement)with sound overall shape and temporarily detailed surface compared with a software solution(SURE)for multi-view stereo.
文摘The dispersoid phase Al_(20)Cu_2Mn_3 in a 2024 Al alloy is commonly composed of twins,An ob- servation of corresponding high resolution image shows that the twin boundary plane is a glide plane other than mirror one.Two neighbouring components of twins are not symmetry of re- flection or rotation,but of glide reflection.The“diamond”glide plane is(101)and the glide vector is(1/4)(-).Components of twins in the phase take shape of prism with the longitudinal edge being parallel to[010]and side faces being{101}and{100}.
基金Supported by the Key Research and Development Plan of Shaanxi Province,No.2021SF-298.
文摘BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and HFS caused by NVC. The judgement of NVC is a critical step in the preoperative evaluation of MVD, which is related to the effect of MVD treatment. Magnetic resonance imaging(MRI) technology has been used to detect NVC prior to MVD for several years. Among many MRI sequences, three-dimensional time-of-flight magnetic resonance angiography(3D TOF MRA) is the most widely used. However, 3D TOF MRA has some shortcomings in detecting NVC. Therefore, 3D TOF MRA combined with high resolution T2-weighted imaging(HR T2WI) is considered to be a more effective method to detect NVC.AIM To determine the value of 3D TOF MRA combined with HR T2WI in the judgment of NVC, and thus to assess its value in the preoperative evaluation of MVD.METHODS Related studies published from inception to September 2022 based on PubMed, Embase, Web of Science, and the Cochrane Library were retrieved. Studies that investigated 3D TOF MRA combined with HR T2WI to judge NVC in patients with TN or HFS were included according to the inclusion criteria. Studies without complete data or not relevant to the research topics were excluded. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to assess the quality of included studies. The publication bias of the included literature was examined by Deeks’ test. An exact binomial rendition of the bivariate mixed-effects regression model was used to synthesize data. Data analysis was performed using the MIDAS module of statistical software Stata 16.0. Two independent investigators extracted patient and study characteristics, and discrepancies were resolved by consensus. Individual and pooled sensitivities and specificities were calculated. The I_(2) statistic and Q test were used to test heterogeneity. The study was registered on the website of PROSERO(registration No. CRD42022357158).RESULTS Our search identified 595 articles, of which 12(including 855 patients) fulfilled the inclusion criteria. Bivariate analysis showed that the pooled sensitivity and specificity of 3D TOF MRA combined with HR T2WI for detecting NVC were 0.96 [95% confidence interval(CI): 0.92-0.98] and 0.92(95%CI: 0.74-0.98), respectively. The pooled positive likelihood ratio was 12.4(95%CI: 3.2-47.8), pooled negative likelihood ratio was 0.04(95%CI: 0.02-0.09), and pooled diagnostic odds ratio was 283(95%CI: 50-1620). The area under the receiver operating characteristic curve was 0.98(95%CI: 0.97-0.99). The studies showed no substantial heterogeneity(I2 = 0, Q = 0.001 P = 0.50).CONCLUSION Our results suggest that 3D TOF MRA combined with HR T2WI has excellent sensitivity and specificity for judging NVC in patients with TN or HFS. This method can be used as an effective tool for preoperative evaluation of MVD.
文摘In the process of image transmission, the famous JPEG and JPEG-2000 compression methods need more transmission time as it is difficult for them to compress the image with a low compression rate. Recently the compressed sensing（CS） theory was proposed, which has earned great concern as it can compress an image with a low compression rate, meanwhile the original image can be perfectly reconstructed from only a few compressed data. The CS theory is used to transmit the high resolution astronomical image and build the simulation environment where there is communication between the satellite and the Earth. Number experimental results show that the CS theory can effectively reduce the image transmission and reconstruction time. Even with a very low compression rate, it still can recover a higher quality astronomical image than JPEG and JPEG-2000 compression methods.
基金National Natural Science Foundation of China(62405256)Hong Kong Research Grants Council General Research Fund(15224921,15223522,15237924)+2 种基金Hong Kong Research Grants Council Collaborative Research Fund(C5047-24G)Basic and Applied Basic Research Foundation of Guangdong Province(2023A1515010831,2025A1515011411)The Hong Kong Polytechnic University(1-CDJA,1-WZ4M).
文摘Single-pixel imaging(SPI)through complex media remains challenging.In this paper,we report high-resolution common-path SPI with dual polarization using random-frequency-encoded time sequences in complex environments where the illumination and detection paths are severely distorted.By leveraging a common-path optical configuration with orthogonal polarization states,a series of dynamic scaling factors can be corrected.The designed random-frequency encoding scheme disperses scattering-induced noise into artifacts to be simply removed.It is demonstrated in optical experiments that the proposed method is feasible and effective to reconstruct highresolution object images in complex environments.The proposed method does not require complex optical components and prior knowledge about scattering media,providing a robust solution for high-resolution optical imaging in complex scenarios where the illumination and detection paths are severely distorted at the same time.
基金National Research Foundation of Korea(RS2024-00401786,RS-2023-00208888).
文摘Achieving clear and deep tissue imaging with optical coherence tomography(OCT)necessitates the simultaneous optimization of three critical factors:high resolution,extended depth of focus(DOF),and high signal-tonoise ratio(SNR).Conventional OCT systems often compromise one or more of these factors,due to inherent trade-offs in optical design and noise management.To address these limitations,we present a chromatic OCT system that simultaneously optimizes all three parameters.The system achieves an isotropic spatial resolution of 2 to 3μm by leveraging a broad bandwidth light source and high-numerical-aperture optics with a pronounced chromatic focal shift,which enables up to a sevenfold DOF extension.Additionally,a novel noise-gating algorithm suppresses system-inherent noise,sidelobe artifacts,and multiple scattering effects,significantly enhancing the SNR.Comparative simulations and experiments demonstrate that the proposed chromatic OCT outperforms conventional high-resolution systems by maintaining superior resolution and SNR over an extended imaging range.These advancements establish chromatic OCT as a powerful tool for high-resolution,deep tissue imaging in biomedical applications,offering improved diagnostic capabilities.
基金Source of Support： This study was supported by grants from China Postdoctoral Science Foundation （No. 2014M562633）, China-Japan Friendship Hospital Youth Science and Technology Excellence Project （No. 2014-QNYC-A-04）, National Natural Science Foundation of China （No. 81173595, 30670731, 81070925, and 81471767）, and National Basic Research Program （973 Program） of China （No. 2013CB733805）.
文摘Background：There are few studies for evaluating wall characteristics of intracranial vertebral artery hypoplasia （VAH）.The aim of this study was to determine wall characteristics of VAH with three-dimensional volumetric isotropic turbo spin echo acquisition （3D VISTA） images and differentiate between acquired atherosclerotic stenosis and VAH.Methods：Thirty patients with suspicious VAH by luminograms were retrospectively enrolled between January 2014 and February 2015.The patients were classified as ＂acquired atherosclerotic stenosis＂ or ＂VAH＂ based on 3D VISTA images.The wall characteristics of VAH were assessed to determine the presence of atherosclerotic lesions,and the patients were classified into two subgroups （VAH with atherosclerosis and VAH with normal wall）.Wall characteristics of basilar arteries and vertebral arteries were also assessed.The clinical and wall characteristics were compared between the two groups.Results：Five of 30 patients with suspicious VAH were finally diagnosed as acquired atherosclerotic stenosis by 3D VISTA images.25 patients were finally diagnosed as VAH including 16 （64.00%） patients with atherosclerosis and 9 （36.00%） patients with normal wall.In the 16 patients with atherosclerosis,plaque was found in 9 patients,slight wall thickening in 6 patients,and thrombus and wall thickening in 1 patient.Compared with VAH patients with normal wall,VAH patients with atherosclerosis showed atherosclerotic basilar arteries and dominant vertebral arteries more frequently （P =0.000）.Conclusions：Three-dimensional VISTA images enable differentiation between the acquired atherosclerotic stenosis and VAH.VAH was also prone to atherosclerotic processes.
文摘Spectral imaging—a suite of techniques combining image acquisition with extremely high color resolution—plays an ever-increasing role in many fields,such as biomedicine,agriculture,geology,archeology,and environmental control.^(1-3)The capability of visualizing,in real time,a tissue or terrain with spatially resolved chemical sensitivity can literally mean the difference between life and death.To appreciate the significance,consider how in vivo spectroscopic sensing of malignant tissue empowers the surgeon to minimize collateral damage during tumor removal while keeping the risk of cancer recurrence low.
基金This study was partly supported by the National Basic Research of China:Project G1998040907.
文摘Fourier series analysis is proposed as a new technique to address the problem of“sub-pixel motion”in deriving cloud motion winds(CMW)from high temporal resolution images.Based on a concept different from that of maximum correlation matching technique,the Fourier technique computes phase speed as an estimate of cloud motion.It is very effective for tracking small cellular clouds in 1-min interval images and more efficient for computation than the maximum correlation technique because only two templates in same size are involved in primary tracking procedure. Moreover it obtains not only CMW vectors but potentially also velocity spectrum and variance.A practical example is given to show the cloud motion winds from 1-min interval images with the Fourier method versus those from traditional 30-min interval images with maximum correlation technique.Problems that require further investigation before the Fourier technique can be regarded as a viable technique,especially for cloud tracking with high temporal resolution images,are also revealed.
基金supported by Spanish Ministry of Economy and Competitiveness and the European Union FEDER funds[grant number AGL2014-56017-R].
文摘While impressive direct geolocation accuracies better than 5.0 m CE90(90%of circular error)can be achieved from the last DigitalGlobe’s Very High Resolution(VHR)satellites(i.e.GeoEye-1 and WorldView-1/2/3/4),it is insufficient for many precise geodetic applications.For these sensors,the best horizontal geopositioning accuracies(around 0.55 m CE90)can be attained by using third-order 3D rational functions with vendor’s rational polynomial coefficients data refined by a zero-order polynomial adjustment obtained from a small number of very accurate ground control points(GCPs).However,these high-quality GCPs are not always available.In this work,two different approaches for improving the initial direct geolocation accuracy of VHR satellite imagery are proposed.Both of them are based on the extraction of three-dimensional GCPs from freely available ancillary data at global coverage such as multi-temporal information of Google Earth and the Shuttle Radar Topography Mission 30 m digital elevation model.The application of these approaches on WorldView-2 and GeoEye-1 stereo pairs over two different study sites proved to improve the horizontal direct geolocation accuracy values around of 75%.
基金supported by the Chinese Academy of Sciences Project for Young Scientists in Basic Research(YSBR067)the Natural Science Foundation of Jiangsu Province(BK20240024)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Y2023087)。
文摘Mesoscopy refers to imaging methodologies that provide a field of view(FOV)ranging from several millimeters to centimeters while achieving cellular or even subcellular resolution(Figure 1).This technological framework employs specially designed large-scale objective lenses to correct aberrations across extended FOVs,synchronized with light-field acquisition modalities through either scanning point detection or large-format array detection.Conventional microscopes,constrained by the limitations of objective lenses,exhibit a trade-off between the FOV and resolution.To achieve both high resolution and a large FOV,common approaches such as FOV stitching and Fourier ptychography were employed.However,these methods were extremely slow and imposed numerous constraints on samples.In 2016,a mesoscopic objective lens was introduced to address these challenges,achieving a 6 mm FOV and 0.7 mm resolution,thereby increasing the imaging throughput of conventional objective lenses by orders of magnitude.1 In the same year,this technology was recognized as one of the top ten physics breakthroughs worldwide by Physics World.Since then,mesoscopic imaging technology has gradually gained momentum and has been applied in various fields.
文摘In the field of optoelectronics,certain types of data may be difficult to accurately annotate,such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges.Weakly supervised learning can provide a more reliable approach in these situations.Current popular approaches mainly adopt the classification-based class activation maps(CAM)as initial pseudo labels to solve the task.
文摘Introduction of the stepwise phase dispersion compensation layer allowed broadband achromatic metalens to have a high numerical aperture,which enabled high-resolution metalens imaging.
