Underwater target detection in forward-looking sonar(FLS)images is a challenging but promising endeavor.The existing neural-based methods yield notable progress but there remains room for improvement due to overlookin...Underwater target detection in forward-looking sonar(FLS)images is a challenging but promising endeavor.The existing neural-based methods yield notable progress but there remains room for improvement due to overlooking the unique characteristics of underwater environments.Considering the problems of low imaging resolution,complex background environment,and large changes in target imaging of underwater sonar images,this paper specifically designs a sonar images target detection Network based on Progressive sensitivity capture,named ProNet.It progressively captures the sensitive regions in the current image where potential effective targets may exist.Guided by this basic idea,the primary technical innovation of this paper is the introduction of a foundational module structure for constructing a sonar target detection backbone network.This structure employs a multi-subspace mixed convolution module that initially maps sonar images into different subspaces and extracts local contextual features using varying convolutional receptive fields within these heterogeneous subspaces.Subsequently,a Scale-aware aggregation module effectively aggregates the heterogeneous features extracted from different subspaces.Finally,the multi-scale attention structure further enhances the relational perception of the aggregated features.We evaluated ProNet on three FLS datasets of varying scenes,and experimental results indicate that ProNet outperforms the current state-of-the-art sonar image and general target detectors.展开更多
Neutron capture event imaging is a novel technique that has the potential to substantially enhance the resolution of existing imaging systems.This study provides a measurement method for neutron capture event distribu...Neutron capture event imaging is a novel technique that has the potential to substantially enhance the resolution of existing imaging systems.This study provides a measurement method for neutron capture event distribution along with multiple reconstruction methods for super-resolution imaging.The proposed technology reduces the point-spread function of an imag-ing system through single-neutron detection and event reconstruction,thereby significantly improving imaging resolution.A single-neutron detection experiment was conducted using a highly practical and efficient^(6)LiF-ZnS scintillation screen of a cold neutron imaging device in the research reactor.In milliseconds of exposure time,a large number of weak light clusters and their distribution in the scintillation screen were recorded frame by frame,to complete single-neutron detection.Several reconstruction algorithms were proposed for the calculations.The location of neutron capture was calculated using several processing methods such as noise removal,filtering,spot segmentation,contour analysis,and local positioning.The proposed algorithm achieved a higher imaging resolution and faster reconstruction speed,and single-neutron super-resolution imaging was realized by combining single-neutron detection experiments and reconstruction calculations.The results show that the resolution of the 100μm thick^(6)LiF-ZnS scintillation screen can be improved from 125 to 40 microns.This indicates that the proposed single-neutron detection and calculation method is effective and can significantly improve imaging resolution.展开更多
A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D po...A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D points can be easily obtained when capturing original 3-D images. The iterative least-mean-squared （LMS） algorithm is applied to optimizing adaptively the transformation matrix parameters. These can effectively improve the registration performance and hurry up the matching process. Experimental results show that it can reach a good subjective impression on aligned 3-D images. Although the algorithm focuses primarily on the human head model, it can also be used for other objects with small modifications.展开更多
Remote Sensing data, as an essential urban basic information in urban planning, has the characteristics of large information capacity, real time, high update speed and accuracy. Because of urban spatial information in...Remote Sensing data, as an essential urban basic information in urban planning, has the characteristics of large information capacity, real time, high update speed and accuracy. Because of urban spatial information involving multi-faceted public and public interests, its data security is very important. The use of digital watermarking technology can effectively protect the secu-rity of urban planning basic data. In practical applications, the “screen capture” poses a great threat to the security of remote sensing image. In order to resist the screen capture attacks, the QR code watermark information is encoded and converted, and combined with a circular angle template watermark, a digital watermarking algorithm for remote sensing images in urban planning information management is proposed. And the proposed algorithm is experimentally verified. Experiments show that the algorithm is robust against screen capture attacks, and provide security guarantee for urban construction and management.展开更多
This work demonstrates a micron-sized nanosecond current pulse probe using a quantum diamond magnetometer.A micron-sized diamond crystal affixed to a fiber tip is integrated on the end of a conical waveguide.We demons...This work demonstrates a micron-sized nanosecond current pulse probe using a quantum diamond magnetometer.A micron-sized diamond crystal affixed to a fiber tip is integrated on the end of a conical waveguide.We demonstrate real-time visualization of a single 100 nanosecond pulse and discrimination of two pulse trains of different frequencies with a coplanar waveguide and a home-made PCB circuit.This technique finds promising applications in the display of electronic stream and can be used as a pulse discriminator to simultaneously receive and demodulate multiple pulse frequencies.This method of detecting pulse current is expected to provide further detailed analysis of the internal working state of the chip.展开更多
To ensure project safety and secure public support, an integrated and comprehensive monitoring program is needed within a carbon capture and storage(CCS) project. Monitoring can be done using many well-established tec...To ensure project safety and secure public support, an integrated and comprehensive monitoring program is needed within a carbon capture and storage(CCS) project. Monitoring can be done using many well-established techniques from various fields, and the seismic method proves to be the crucial one. This method is widely used to determine the CO_(2) distribution, image the plume development, and quantitatively estimate the concentration. Because both the CO_(2) distribution and the potential migration pathway can be spatially small scale, high resolution for seismic imaging is demanded. However, obtaining a high-resolution image of a subsurface structure in marine settings is difficult. Herein, we introduce the novel Hcable(Harrow-like cable system) technique, which may be applied to offshore CCS monitoring. This technique uses a highfrequency source(the dominant frequency>100 Hz) to generate seismic waves and a combination of a long cable and several short streamers to receive seismic waves. Ultrahigh-frequency seismic images are achieved through the processing of Hcable seismic data. Hcable is then applied in a case study to demonstrate its detailed characterization for small-scale structures. This work reveals that Hcable is a promising tool for timelapse seismic monitoring of oceanic CCS.展开更多
Background This study presents a neural hand reconstruction method for monocular 3D hand pose and shape estimation.Methods Alternate to directly representing hand with 3D data,a novel UV position map is used to repres...Background This study presents a neural hand reconstruction method for monocular 3D hand pose and shape estimation.Methods Alternate to directly representing hand with 3D data,a novel UV position map is used to represent a hand pose and shape with 2D data that maps 3D hand surface points to 2D image space.Furthermore,an encoder-decoder neural network is proposed to infer such UV position map from a single image.To train this network with inadequate ground truth training pairs,we propose a novel MANOReg module that employs MANO model as a prior shape to constrain high dimensional space of the UV position map.Results The quantitative and qualitative experiments demonstrate the effectiveness of our UV position map representation and MANOReg module.展开更多
Potassium carbonate-based sorbents are prospective materials for direct air capture(DAC).In the present study,we examined and revealed the influence of the temperature swing adsorption(TSA)cycle conditions on the CO_(...Potassium carbonate-based sorbents are prospective materials for direct air capture(DAC).In the present study,we examined and revealed the influence of the temperature swing adsorption(TSA)cycle conditions on the CO_(2) sorption properties of a novel aerogel-based K_(2)CO_(3)/ZrO_(2) sorbent in a DAC process.It was shown that the humidity and temperature drastically affect the sorption dynamic and sorption capacity of the sorbent.When a temperature at the sorption stage was 29℃ and a water vapor pressure P_(H2O) in the feed air was 5.2 mbar(1 bar=105 Pa),the composite material demonstrated a stable CO_(2) sorption capacity of 3.4%(mass).An increase in sorption temperature leads to a continuous decrease in the CO_(2) absorption capacity reaching a value of 0.7%(mass)at T=80℃.The material showed the retention of a stable CO_(2) sorption capacity for many cycles at each temperature in the range.Increasing PH2O in the inlet air from 5.2 to 6.8 mbar leads to instability of CO_(2) sorption capacity which decreases in the course of 3 consecutive TSA cycles from 1.7%to 0.8%(mass)at T=29℃.A further increase in air humidity only facilitates the deterioration of the CO_(2) sorption capacity of the material.A possible explanation for this phenomenon could be the filling of the porous system of the sorbent with solid reaction products and an aqueous solution of potassium salts,which leads to a significant slowdown in the CO_(2) diffusion in the composite sorbent grain.To investigate the regeneration step of the TSA cycle in situ,the macro ATRFTIR(attenuated total reflection Fourier-transform infrared)spectroscopic imaging was applied for the first time.It was shown that the migration of carbonate-containing species over the surface of sorbent occurs during the thermal regeneration stage of the TSA cycle.The movement of the active component in the porous matrix of the sorbent can affect the sorption characteristics of the composite material.The revealed features make it possible to formulate the requirements and limitations that need to be taken into account for the practical implementation of the DAC process using the K_(2)CO_(3)/ZrO_(2) composite sorbent.展开更多
The visible-light imaging system used in military equipment is often subjected to severe weather conditions, such as fog, haze, and smoke, under complex lighting conditions at night that significantly degrade the acqu...The visible-light imaging system used in military equipment is often subjected to severe weather conditions, such as fog, haze, and smoke, under complex lighting conditions at night that significantly degrade the acquired images. Currently available image defogging methods are mostly suitable for environments with natural light in the daytime, but the clarity of images captured under complex lighting conditions and spatial changes in the presence of fog at night is not satisfactory. This study proposes an algorithm to remove night fog from single images based on an analysis of the statistical characteristics of images in scenes involving night fog. Color channel transfer is designed to compensate for the high attenuation channel of foggy images acquired at night. The distribution of transmittance is estimated by the deep convolutional network DehazeNet, and the spatial variation of atmospheric light is estimated in a point-by-point manner according to the maximum reflection prior to recover the clear image. The results of experiments show that the proposed method can compensate for the high attenuation channel of foggy images at night, remove the effect of glow from a multi-color and non-uniform ambient source of light, and improve the adaptability and visual effect of the removal of night fog from images compared with the conventional method.展开更多
On-orbit service is important for maintaining the sustainability of the space environment.A space-based visible camera is an economical and lightweight sensor for situational awareness during on-orbit service.However,...On-orbit service is important for maintaining the sustainability of the space environment.A space-based visible camera is an economical and lightweight sensor for situational awareness during on-orbit service.However,it can be easily affected by the low illumination environment.Recently,deep learning has achieved remarkable success in image enhancement of natural images,but it is seldom applied in space due to the data bottleneck.In this study,we first propose a dataset of BeiDou navigation satellites for on-orbit low-light image enhancement(LLIE).In the automatic data collection scheme,we focus on reducing the domain gap and improving the diversity of the dataset.We collect hardware-in-the-loop images based on a robotic simulation testbed imitating space lighting conditions.To evenly sample poses of different orientations and distances without collision,we propose a collision-free workspace and pose-stratified sampling.Subsequently,we develop a novel diffusion model.To enhance the image contrast without over-exposure and blurred details,we design fused attention guidance to highlight the structure and the dark region.Finally,a comparison of our method with previous methods indicates that our method has better on-orbit LLIE performance.展开更多
基金supported in part by Youth Innovation Promotion Association,Chinese Academy of Sciences under Grant 2022022in part by South China Sea Nova project of Hainan Province under Grant NHXXRCXM202340in part by the Scientific Research Foundation Project of Hainan Acoustics Laboratory under grant ZKNZ2024001.
文摘Underwater target detection in forward-looking sonar(FLS)images is a challenging but promising endeavor.The existing neural-based methods yield notable progress but there remains room for improvement due to overlooking the unique characteristics of underwater environments.Considering the problems of low imaging resolution,complex background environment,and large changes in target imaging of underwater sonar images,this paper specifically designs a sonar images target detection Network based on Progressive sensitivity capture,named ProNet.It progressively captures the sensitive regions in the current image where potential effective targets may exist.Guided by this basic idea,the primary technical innovation of this paper is the introduction of a foundational module structure for constructing a sonar target detection backbone network.This structure employs a multi-subspace mixed convolution module that initially maps sonar images into different subspaces and extracts local contextual features using varying convolutional receptive fields within these heterogeneous subspaces.Subsequently,a Scale-aware aggregation module effectively aggregates the heterogeneous features extracted from different subspaces.Finally,the multi-scale attention structure further enhances the relational perception of the aggregated features.We evaluated ProNet on three FLS datasets of varying scenes,and experimental results indicate that ProNet outperforms the current state-of-the-art sonar image and general target detectors.
基金supported by the National Natural Science Foundation of China(Nos.12205271,12075217,U20B2011,and 51978218)Sichuan Science and Technology Program(No.2019ZDZX0010)the National Key R&D Program of China(No.2022YFA1604002).
文摘Neutron capture event imaging is a novel technique that has the potential to substantially enhance the resolution of existing imaging systems.This study provides a measurement method for neutron capture event distribution along with multiple reconstruction methods for super-resolution imaging.The proposed technology reduces the point-spread function of an imag-ing system through single-neutron detection and event reconstruction,thereby significantly improving imaging resolution.A single-neutron detection experiment was conducted using a highly practical and efficient^(6)LiF-ZnS scintillation screen of a cold neutron imaging device in the research reactor.In milliseconds of exposure time,a large number of weak light clusters and their distribution in the scintillation screen were recorded frame by frame,to complete single-neutron detection.Several reconstruction algorithms were proposed for the calculations.The location of neutron capture was calculated using several processing methods such as noise removal,filtering,spot segmentation,contour analysis,and local positioning.The proposed algorithm achieved a higher imaging resolution and faster reconstruction speed,and single-neutron super-resolution imaging was realized by combining single-neutron detection experiments and reconstruction calculations.The results show that the resolution of the 100μm thick^(6)LiF-ZnS scintillation screen can be improved from 125 to 40 microns.This indicates that the proposed single-neutron detection and calculation method is effective and can significantly improve imaging resolution.
文摘A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D points can be easily obtained when capturing original 3-D images. The iterative least-mean-squared （LMS） algorithm is applied to optimizing adaptively the transformation matrix parameters. These can effectively improve the registration performance and hurry up the matching process. Experimental results show that it can reach a good subjective impression on aligned 3-D images. Although the algorithm focuses primarily on the human head model, it can also be used for other objects with small modifications.
文摘Remote Sensing data, as an essential urban basic information in urban planning, has the characteristics of large information capacity, real time, high update speed and accuracy. Because of urban spatial information involving multi-faceted public and public interests, its data security is very important. The use of digital watermarking technology can effectively protect the secu-rity of urban planning basic data. In practical applications, the “screen capture” poses a great threat to the security of remote sensing image. In order to resist the screen capture attacks, the QR code watermark information is encoded and converted, and combined with a circular angle template watermark, a digital watermarking algorithm for remote sensing images in urban planning information management is proposed. And the proposed algorithm is experimentally verified. Experiments show that the algorithm is robust against screen capture attacks, and provide security guarantee for urban construction and management.
基金Project supported by the National Key R&D Program of China(Grant No.2021YFB2012600)。
文摘This work demonstrates a micron-sized nanosecond current pulse probe using a quantum diamond magnetometer.A micron-sized diamond crystal affixed to a fiber tip is integrated on the end of a conical waveguide.We demonstrate real-time visualization of a single 100 nanosecond pulse and discrimination of two pulse trains of different frequencies with a coplanar waveguide and a home-made PCB circuit.This technique finds promising applications in the display of electronic stream and can be used as a pulse discriminator to simultaneously receive and demodulate multiple pulse frequencies.This method of detecting pulse current is expected to provide further detailed analysis of the internal working state of the chip.
基金Supported by the project of Sanya Yazhou Bay Science and Technology City (Grant No:SCKJ-JYRC-2022-14)。
文摘To ensure project safety and secure public support, an integrated and comprehensive monitoring program is needed within a carbon capture and storage(CCS) project. Monitoring can be done using many well-established techniques from various fields, and the seismic method proves to be the crucial one. This method is widely used to determine the CO_(2) distribution, image the plume development, and quantitatively estimate the concentration. Because both the CO_(2) distribution and the potential migration pathway can be spatially small scale, high resolution for seismic imaging is demanded. However, obtaining a high-resolution image of a subsurface structure in marine settings is difficult. Herein, we introduce the novel Hcable(Harrow-like cable system) technique, which may be applied to offshore CCS monitoring. This technique uses a highfrequency source(the dominant frequency>100 Hz) to generate seismic waves and a combination of a long cable and several short streamers to receive seismic waves. Ultrahigh-frequency seismic images are achieved through the processing of Hcable seismic data. Hcable is then applied in a case study to demonstrate its detailed characterization for small-scale structures. This work reveals that Hcable is a promising tool for timelapse seismic monitoring of oceanic CCS.
文摘Background This study presents a neural hand reconstruction method for monocular 3D hand pose and shape estimation.Methods Alternate to directly representing hand with 3D data,a novel UV position map is used to represent a hand pose and shape with 2D data that maps 3D hand surface points to 2D image space.Furthermore,an encoder-decoder neural network is proposed to infer such UV position map from a single image.To train this network with inadequate ground truth training pairs,we propose a novel MANOReg module that employs MANO model as a prior shape to constrain high dimensional space of the UV position map.Results The quantitative and qualitative experiments demonstrate the effectiveness of our UV position map representation and MANOReg module.
基金This work was supported by Russian Science Foundation(19-73-00079).The authors also thank Leonova A.A.for performing N2 adsorption measurements.
文摘Potassium carbonate-based sorbents are prospective materials for direct air capture(DAC).In the present study,we examined and revealed the influence of the temperature swing adsorption(TSA)cycle conditions on the CO_(2) sorption properties of a novel aerogel-based K_(2)CO_(3)/ZrO_(2) sorbent in a DAC process.It was shown that the humidity and temperature drastically affect the sorption dynamic and sorption capacity of the sorbent.When a temperature at the sorption stage was 29℃ and a water vapor pressure P_(H2O) in the feed air was 5.2 mbar(1 bar=105 Pa),the composite material demonstrated a stable CO_(2) sorption capacity of 3.4%(mass).An increase in sorption temperature leads to a continuous decrease in the CO_(2) absorption capacity reaching a value of 0.7%(mass)at T=80℃.The material showed the retention of a stable CO_(2) sorption capacity for many cycles at each temperature in the range.Increasing PH2O in the inlet air from 5.2 to 6.8 mbar leads to instability of CO_(2) sorption capacity which decreases in the course of 3 consecutive TSA cycles from 1.7%to 0.8%(mass)at T=29℃.A further increase in air humidity only facilitates the deterioration of the CO_(2) sorption capacity of the material.A possible explanation for this phenomenon could be the filling of the porous system of the sorbent with solid reaction products and an aqueous solution of potassium salts,which leads to a significant slowdown in the CO_(2) diffusion in the composite sorbent grain.To investigate the regeneration step of the TSA cycle in situ,the macro ATRFTIR(attenuated total reflection Fourier-transform infrared)spectroscopic imaging was applied for the first time.It was shown that the migration of carbonate-containing species over the surface of sorbent occurs during the thermal regeneration stage of the TSA cycle.The movement of the active component in the porous matrix of the sorbent can affect the sorption characteristics of the composite material.The revealed features make it possible to formulate the requirements and limitations that need to be taken into account for the practical implementation of the DAC process using the K_(2)CO_(3)/ZrO_(2) composite sorbent.
基金supported by a grant from the Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology (Grant No. GZZKFJJ2020004)the National Natural Science Foundation of China (Grant Nos. 61875013 and 61827814)the Natural Science Foundation of Beijing Municipality (Grant No. Z190018)。
文摘The visible-light imaging system used in military equipment is often subjected to severe weather conditions, such as fog, haze, and smoke, under complex lighting conditions at night that significantly degrade the acquired images. Currently available image defogging methods are mostly suitable for environments with natural light in the daytime, but the clarity of images captured under complex lighting conditions and spatial changes in the presence of fog at night is not satisfactory. This study proposes an algorithm to remove night fog from single images based on an analysis of the statistical characteristics of images in scenes involving night fog. Color channel transfer is designed to compensate for the high attenuation channel of foggy images acquired at night. The distribution of transmittance is estimated by the deep convolutional network DehazeNet, and the spatial variation of atmospheric light is estimated in a point-by-point manner according to the maximum reflection prior to recover the clear image. The results of experiments show that the proposed method can compensate for the high attenuation channel of foggy images at night, remove the effect of glow from a multi-color and non-uniform ambient source of light, and improve the adaptability and visual effect of the removal of night fog from images compared with the conventional method.
基金Project supported by the National Natural Science Foundation of China(Nos.62403242 and 61973167)the Fundamental Research Funds for the Central Universities(No.30924010932)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX23_0481)。
文摘On-orbit service is important for maintaining the sustainability of the space environment.A space-based visible camera is an economical and lightweight sensor for situational awareness during on-orbit service.However,it can be easily affected by the low illumination environment.Recently,deep learning has achieved remarkable success in image enhancement of natural images,but it is seldom applied in space due to the data bottleneck.In this study,we first propose a dataset of BeiDou navigation satellites for on-orbit low-light image enhancement(LLIE).In the automatic data collection scheme,we focus on reducing the domain gap and improving the diversity of the dataset.We collect hardware-in-the-loop images based on a robotic simulation testbed imitating space lighting conditions.To evenly sample poses of different orientations and distances without collision,we propose a collision-free workspace and pose-stratified sampling.Subsequently,we develop a novel diffusion model.To enhance the image contrast without over-exposure and blurred details,we design fused attention guidance to highlight the structure and the dark region.Finally,a comparison of our method with previous methods indicates that our method has better on-orbit LLIE performance.
