The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions a...The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.展开更多
Imaging is an important method for astronomy research.In practice,original images acquired by a telescope are often convolved and blurred by the point-spread function(PSF),which is a very unfavorable situation for man...Imaging is an important method for astronomy research.In practice,original images acquired by a telescope are often convolved and blurred by the point-spread function(PSF),which is a very unfavorable situation for many scientific studies including astronomy.This paper introduced a single equation iterative method for solving complex linear equations,and this method can deconvolute dirty images,eliminate the effects of the PSF well.With different PSFs,this algorithm shows very good results in deconvolution.Also,with a giant PSF of aperture synthesis imaging,this algorithm improves the peak signal-to-noise ratio and structural similarity of the dirty images by 41.0%and 33.9%on average.In addition,this paper proves that the algorithm can deconvolute the dirty image by making full use of the information of each pixel in the image,even if the dirty image has salt and pepper noise or even lost areas;by its excellent properties of flexible operation to a single pixel,all these bad situations can be dealt with and the image can be restored.展开更多
Data hiding methods involve embedding secret messages into cover objects to enable covert communication in a way that is difficult to detect.In data hiding methods based on image interpolation,the image size is reduce...Data hiding methods involve embedding secret messages into cover objects to enable covert communication in a way that is difficult to detect.In data hiding methods based on image interpolation,the image size is reduced and then enlarged through interpolation,followed by the embedding of secret data into the newly generated pixels.A general improving approach for embedding secret messages is proposed.The approach may be regarded a general model for enhancing the data embedding capacity of various existing image interpolation-based data hiding methods.This enhancement is achieved by expanding the range of pixel values available for embedding secret messages,removing the limitations of many existing methods,where the range is restricted to powers of two to facilitate the direct embedding of bit-based messages.This improvement is accomplished through the application of multiple-based number conversion to the secret message data.The method converts the message bits into a multiple-based number and uses an algorithm to embed each digit of this number into an individual pixel,thereby enhancing the message embedding efficiency,as proved by a theorem derived in this study.The proposed improvement method has been tested through experiments on three well-known image interpolation-based data hiding methods.The results show that the proposed method can enhance the three data embedding rates by approximately 14%,13%,and 10%,respectively,create stego-images with good quality,and resist RS steganalysis attacks.These experimental results indicate that the use of the multiple-based number conversion technique to improve the three interpolation-based methods for embedding secret messages increases the number of message bits embedded in the images.For many image interpolation-based data hiding methods,which use power-of-two pixel-value ranges for message embedding,other than the three tested ones,the proposed improvement method is also expected to be effective for enhancing their data embedding capabilities.展开更多
Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(...Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(FIR)”method for multi-sourced depth data fusion,and used it to merge the electronic nautical chart dataset(referred to as Chart2014 in this paper)with the global digital elevation dataset(referred to as Globalbath2002 in this paper).Compared to the traditional fusion of two datasets by direct combination and interpolation,the new Grid-DEM formed by FIR can better represent the data characteristics of Chart2014,reduce the calculation difficulty,and be more intuitive,and,the choice of different interpolation methods in FIR and the influence of the“exclusion radius R”parameter were discussed.FIR avoids complex calculations of spatial distances among points from different sources,and instead uses spatial exclusion map to perform one-step screening based on the exclusion radius R,which greatly improved the fusion status of a reliable dataset.The fusion results of different experiments were analyzed statistically with root mean square error and mean relative error,showing that the interpolation methods based on Delaunay triangulation are more suitable for the fusion of nautical chart depth of China,and factors such as the point density distribution of multiple source data,accuracy,interpolation method,and various terrain conditions should be fully considered when selecting the exclusion radius R.展开更多
Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time perfor...Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.展开更多
The in-flight calibration and performance of the Solar Disk Imager(SDI),which is a pivotal instrument of the LyαSolar Telescope onboard the Advanced Space-based Solar Observatory mission,suggested a much lower spatia...The in-flight calibration and performance of the Solar Disk Imager(SDI),which is a pivotal instrument of the LyαSolar Telescope onboard the Advanced Space-based Solar Observatory mission,suggested a much lower spatial resolution than expected.In this paper,we developed the SDI point-spread function(PSF)and Image Bivariate Optimization Algorithm(SPIBOA)to improve the quality of SDI images.The bivariate optimization method smartly combines deep learning with optical system modeling.Despite the lack of information about the real image taken by SDI and the optical system function,this algorithm effectively estimates the PSF of the SDI imaging system directly from a large sample of observational data.We use the estimated PSF to conduct deconvolution correction to observed SDI images,and the resulting images show that the spatial resolution after correction has increased by a factor of more than three with respect to the observed ones.Meanwhile,our method also significantly reduces the inherent noise in the observed SDI images.The SPIBOA has now been successfully integrated into the routine SDI data processing,providing important support for the scientific studies based on the data.The development and application of SPIBOA also paves new ways to identify astronomical telescope systems and enhance observational image quality.Some essential factors and precautions in applying the SPIBOA method are also discussed.展开更多
Measuring the transverse velocity field in high-resolution solar images is essential for understanding solar dynamics.This paper introduces an innovative unsupervised deep learning optical flow model designed to calcu...Measuring the transverse velocity field in high-resolution solar images is essential for understanding solar dynamics.This paper introduces an innovative unsupervised deep learning optical flow model designed to calculate the transverse velocity field,addressing the challenges of missing optical flow labels and the limited accuracy of velocity field measurements in high-resolution solar images.The proposed method converts the transverse velocity field computation problem into an optical flow computation problem,using two forward propagations of features to get rid of the reliance on optical flow labels.Additionally,it reduces the impact of the“Brightness Consistency”constraint on optical flow accuracy by identifying and handling optical flow outliers.We apply this method to compute the transverse velocity fields of high-resolution solar image sequences from the Hαand TiO bands,observed by the New Vacuum Solar Telescope.Comparative experiments with several wellestablished optical flow methods,including those based on supervised deep learning models,show that our approach outperforms the comparison methods according to key evaluation metrics such as Residual Map Mean,Residual Map Variance,Cross Correlation,and Structural Similarity Index Measure.Moreover,since optical flow captures the fundamental motion information in image sequences,the proposed method can be applied to a variety of research areas,including solar image registration,sequence alignment,image super-resolution,magnetic field calibration,and solar activity forecasting.The code is available at https://github.com/jackie-willianm/Transverse-Velocity-Field-Measurement-of-Solar-High-Resolution-Images.展开更多
Image captioning has seen significant research efforts over the last decade.The goal is to generate meaningful semantic sentences that describe visual content depicted in photographs and are syntactically accurate.Man...Image captioning has seen significant research efforts over the last decade.The goal is to generate meaningful semantic sentences that describe visual content depicted in photographs and are syntactically accurate.Many real-world applications rely on image captioning,such as helping people with visual impairments to see their surroundings.To formulate a coherent and relevant textual description,computer vision techniques are utilized to comprehend the visual content within an image,followed by natural language processing methods.Numerous approaches and models have been developed to deal with this multifaceted problem.Several models prove to be stateof-the-art solutions in this field.This work offers an exclusive perspective emphasizing the most critical strategies and techniques for enhancing image caption generation.Rather than reviewing all previous image captioning work,we analyze various techniques that significantly improve image caption generation and achieve significant performance improvements,including encompassing image captioning with visual attention methods,exploring semantic information types in captions,and employing multi-caption generation techniques.Further,advancements such as neural architecture search,few-shot learning,multi-phase learning,and cross-modal embedding within image caption networks are examined for their transformative effects.The comprehensive quantitative analysis conducted in this study identifies cutting-edgemethodologies and sheds light on their profound impact,driving forward the forefront of image captioning technology.展开更多
The China Space Station Telescope(CSST)is a 2 m three-mirror anastigmat equipped with a Fast Steering Mirror(FSM),which is part of its precision image stabilization system.The FSM is used to compensate for residuals f...The China Space Station Telescope(CSST)is a 2 m three-mirror anastigmat equipped with a Fast Steering Mirror(FSM),which is part of its precision image stabilization system.The FSM is used to compensate for residuals from the previous stage of the image stabilization system.However,a new type of image stabilization residual caused by image rotation and projection distortion is introduced when the FSM performs tip-tilt adjustments,reducing both the image stabilization accuracy and the absolute pointing accuracy of the CSST.In this paper,we propose a scheme to compute the image stabilization residuals across the full field of view(FOV)by using a reference star as the target for stabilization control,which can be utilized for subsequent image position correction.To achieve this,we developed a linear optical model for image point displacement by simplifying an existing image point displacement model and incorporating more readily available parameters.The computational accuracy of the new model is equivalent to that of the original,with computational differences of less than 0.03μm.Based on this linear model,we established a calculation model for image stabilization residuals,including those due to image rotation and projection distortion caused by FSM tip-tilt adjustments.This model provides a theoretical foundation for quantifying such residuals during the image stabilization process.Finally,the results of testing using this scheme are provided.Experimental results demonstrate that within the observation FOV of the CSST,when the FSM tilts by(1″,1″),the maximum absolute value of the image stabilization residuals accounts for 20%of the total image stabilization accuracy requirement.This finding underscores the necessity of computing and correcting these residuals to meet performance requirements.展开更多
Creating conditions to implement equilibrium processes of damage accumulation under a predictable scenario enables control over the failure of structural elements in critical states.It improves safety and reduces the ...Creating conditions to implement equilibrium processes of damage accumulation under a predictable scenario enables control over the failure of structural elements in critical states.It improves safety and reduces the probability of catastrophic behavior in case of accidents.Equilibrium damage accumulation in some cases leads to a falling part(called a postcritical stage)on the material’s stress-strain curve.It must be taken into account to assess the strength and deformation limits of composite structures.Digital image correlation method,acoustic emission(AE)signals recording,and optical microscopy were used in this paper to study the deformation and failure processes of an orthogonal-layup composite during tension in various directions to orthotropy axes.An elastic-plastic deformation model was proposed for the composite in a plane stress condition.The evolution of strain fields and neck formation were analyzed.The staging of the postcritical deformation process was described.AE signals obtained during tests were studied;characteristic damage types of a material were defined.The rationality and necessity of polymer composites’postcritical deformation stage taken into account in refined strength analysis of structures were concluded.展开更多
In the task of classifying massive celestial data,the accurate classification of galaxies,stars,and quasars usually relies on spectral labels.However,spectral data account for only a small fraction of all astronomical...In the task of classifying massive celestial data,the accurate classification of galaxies,stars,and quasars usually relies on spectral labels.However,spectral data account for only a small fraction of all astronomical observation data,and the target source classification information in vast photometric data has not been accurately measured.To address this,we propose a novel deep learning-based algorithm,YL8C4Net,for the automatic detection and classification of target sources in photometric images.This algorithm combines the YOLOv8 detection network with the Conv4Net classification network.Additionally,we propose a novel magnitude-based labeling method for target source annotation.In the performance evaluation,the YOLOv8 achieves impressive performance with average precision scores of 0.824 for AP@0.5 and 0.795 for AP@0.5:0.95.Meanwhile,the constructed Conv4Net attains an accuracy of 0.8895.Overall,YL8C4Net offers the advantages of fewer parameters,faster processing speed,and higher classification accuracy,making it particularly suitable for large-scale data processing tasks.Furthermore,we employed the YL8C4Net model to conduct target source detection and classification on photometric images from 20 sky regions in SDSS-DR17.As a result,a catalog containing about 9.39 million target source classification results has been preliminarily constructed,thereby providing valuable reference data for astronomical research.展开更多
The Solar Polar-orbit Observatory(SPO),proposed by Chinese scientists,is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small e...The Solar Polar-orbit Observatory(SPO),proposed by Chinese scientists,is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small ellipticity.However,one of the most significant challenges lies in ultra-long-distance data transmission,particularly for the Magnetic and Helioseismic Imager(MHI),which is the most important payload and generates the largest volume of data in SPO.In this paper,we propose a tailored lossless data compression method based on the measurement mode and characteristics of MHI data.The background out of the solar disk is removed to decrease the pixel number of an image under compression.Multiple predictive coding methods are combined to eliminate the redundancy utilizing the correlation(space,spectrum,and polarization)in data set,improving the compression ratio.Experimental results demonstrate that our method achieves an average compression ratio of 3.67.The compression time is also less than the general observation period.The method exhibits strong feasibility and can be easily adapted to MHI.展开更多
The task of indoor visual localization, utilizing camera visual information for user pose calculation, was a core component of Augmented Reality (AR) and Simultaneous Localization and Mapping (SLAM). Existing indoor l...The task of indoor visual localization, utilizing camera visual information for user pose calculation, was a core component of Augmented Reality (AR) and Simultaneous Localization and Mapping (SLAM). Existing indoor localization technologies generally used scene-specific 3D representations or were trained on specific datasets, making it challenging to balance accuracy and cost when applied to new scenes. Addressing this issue, this paper proposed a universal indoor visual localization method based on efficient image retrieval. Initially, a Multi-Layer Perceptron (MLP) was employed to aggregate features from intermediate layers of a convolutional neural network, obtaining a global representation of the image. This approach ensured accurate and rapid retrieval of reference images. Subsequently, a new mechanism using Random Sample Consensus (RANSAC) was designed to resolve relative pose ambiguity caused by the essential matrix decomposition based on the five-point method. Finally, the absolute pose of the queried user image was computed, thereby achieving indoor user pose estimation. The proposed indoor localization method was characterized by its simplicity, flexibility, and excellent cross-scene generalization. Experimental results demonstrated a positioning error of 0.09 m and 2.14° on the 7Scenes dataset, and 0.15 m and 6.37° on the 12Scenes dataset. These results convincingly illustrated the outstanding performance of the proposed indoor localization method.展开更多
In high-resolution cone-beam computed tomography （CBCT） using the flat-panel detector, imperfect or defect detector elements cause ring artifacts due to the none-uniformity of their X-ray response. They often distur...In high-resolution cone-beam computed tomography （CBCT） using the flat-panel detector, imperfect or defect detector elements cause ring artifacts due to the none-uniformity of their X-ray response. They often disturb the image quality. A dedicated fitting correction method for high-resolution micro-CT is presented. The method converts each elementary X-ray response curve to an average one, and eliminates response inconsistency among pixels. Other factors of the method are discussed, such as the correction factor variability by different sampling frames and nonlinear factors over the whole spectrum. Results show that the noise and artifacts are both reduced in reconstructed images展开更多
We conducted a study on the numerical calculation and response analysis of a transient electromagnetic field generated by a ground source in geological media. One solution method, the traditional discrete image method...We conducted a study on the numerical calculation and response analysis of a transient electromagnetic field generated by a ground source in geological media. One solution method, the traditional discrete image method, involves complex operation, and its digital filtering algorithm requires a large number of calculations. To solve these problems, we proposed an improved discrete image method, where the following are realized： the real number of the electromagnetic field solution based on the Gaver-Stehfest algorithm for approximate inversion, the exponential approximation of the objective kernel function using the Prony method, the transient electromagnetic field according to discrete image theory, and closed-form solution of the approximate coefficients. To verify the method, we tentatively calculated the transient electromagnetic field in a homogeneous model and compared it with the results obtained from the Hankel transform digital filtering method. The results show that the method has considerable accuracy and good applicability. We then used this method to calculate the transient electromagnetic field generated by a ground magnetic dipole source in a typical geoelectric model and analyzed the horizontal component response of the induced magnetic field obtained from the ＂ground excitation-stratum measurement method. We reached the conclusion that the horizontal component response of a transient field is related to the geoelectric structure, observation time, spatial location, and others. The horizontal component response of the induced magnetic field reflects the eddy current field distribution and its vertical gradient variation. During the detection of abnormal objects, positions with a zero or comparatively large offset were selected for the drill- hole measurements or a comparatively long observation delay was adopted to reduce the influence of the ambient field on the survey results. The discrete image method and forward calculation results in this paper can be used as references for relevant research.展开更多
A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inne...A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inner-level Bregmanized method devotes to dictionary updating and sparse represention of small overlapping image patches. The introduced constraint of graph regularized sparse coding can capture local image features effectively, and consequently enables accurate reconstruction from highly undersampled partial data. Furthermore, modified sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge within a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can effectively reconstruct images and it outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.展开更多
In this paper,we design an efficient,multi-stage image segmentation framework that incorporates a weighted difference of anisotropic and isotropic total variation(AITV).The segmentation framework generally consists of...In this paper,we design an efficient,multi-stage image segmentation framework that incorporates a weighted difference of anisotropic and isotropic total variation(AITV).The segmentation framework generally consists of two stages:smoothing and thresholding,thus referred to as smoothing-and-thresholding(SaT).In the first stage,a smoothed image is obtained by an AITV-regularized Mumford-Shah(MS)model,which can be solved efficiently by the alternating direction method of multipliers(ADMMs)with a closed-form solution of a proximal operator of the l_(1)-αl_(2) regularizer.The convergence of the ADMM algorithm is analyzed.In the second stage,we threshold the smoothed image by K-means clustering to obtain the final segmentation result.Numerical experiments demonstrate that the proposed segmentation framework is versatile for both grayscale and color images,effcient in producing high-quality segmentation results within a few seconds,and robust to input images that are corrupted with noise,blur,or both.We compare the AITV method with its original convex TV and nonconvex TVP(O<p<1)counterparts,showcasing the qualitative and quantitative advantages of our proposed method.展开更多
We have developed a novel method for co-adding multiple under-sampled images that combines the iteratively reweighted least squares and divide-and-conquer algorithms.Our approach not only allows for the anti-aliasing ...We have developed a novel method for co-adding multiple under-sampled images that combines the iteratively reweighted least squares and divide-and-conquer algorithms.Our approach not only allows for the anti-aliasing of the images but also enables Point-Spread Function(PSF)deconvolution,resulting in enhanced restoration of extended sources,the highest peak signal-to-noise ratio,and reduced ringing artefacts.To test our method,we conducted numerical simulations that replicated observation runs of the China Space Station Telescope/the VLT Survey Telescope(VST)and compared our results to those obtained using previous algorithms.The simulation showed that our method outperforms previous approaches in several ways,such as restoring the profile of extended sources and minimizing ringing artefacts.Additionally,because our method relies on the inherent advantages of least squares fitting,it is more versatile and does not depend on the local uniformity hypothesis for the PSF.However,the new method consumes much more computation than the other approaches.展开更多
The estimation of shear strength of rock mass discontinuity is always a focal, but difficult, problem in the field of geotechnical engineering. Considering the disadvantages and limitation of exist- ing estimation met...The estimation of shear strength of rock mass discontinuity is always a focal, but difficult, problem in the field of geotechnical engineering. Considering the disadvantages and limitation of exist- ing estimation methods, a new approach based on the shadow area percentage （SAP） that can be used to quantify surface roughness is proposed in this article. Firstly, by the help of laser scanning technique, the three-dimensional model of the surface of rock discontinuity was established. Secondly, a light source was simulated, and there would be some shadows produced on the model surface. Thirdly, to obtain the value of SAP of each specimen, the shadow detection technique was introduced for use. Fourthly, compared with the result from direct shear testing and based on statistics, an empirical for- mula was found among SAP, normal stress, and shear strength. Data of Yujian （~ River were used as an example, and the following conclusions have been made. （1） In the case of equal normal stress, the peak shear stress is positively proportional to the SAP. （2） The formula for estimating was derived, and the predictions of peak-shear strength made with this equation well agreed with the experimental re- suits obtained in laboratory tests.展开更多
To segment the tumor region precisely is a prerequisite for ultrasound navigation and treatment. In this paper, a normalized cut method to segment tumor ultrasound image is proposed by means of simple linear iterative...To segment the tumor region precisely is a prerequisite for ultrasound navigation and treatment. In this paper, a normalized cut method to segment tumor ultrasound image is proposed by means of simple linear iterative clustering for presegmentation procedure. The first step, we use simple linear iterative clustering algorithm to divide the image into a number of homogeneous over-segmented regions. Then, these regions are regarded as nodes, and a similarity matrix is constructed by comparing the histograms of each two regions. Finally, we apply the Ncut method to merging the over-segmented regions, then the image segmentation process is completed. The results show that the proposed segmentation scheme handles the strong speckle noise, low contrast, and weak edges well in ultrasound image. Our method has high segmentation precision and computation efficiency than the pixel-based Ncut method.展开更多
基金supported by the National Natural Science(No.U19A2063)the Jilin Provincial Development Program of Science and Technology (No.20230201080GX)the Jilin Province Education Department Scientific Research Project (No.JJKH20230851KJ)。
文摘The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.
基金supported by the National Key R&D Program of China(No.2022YFE0133700)the National Natural Science Foundation of China(NSFC,No.12273007)+4 种基金the Guizhou Provincial Excellent Young Science and Technology Talent Program(No.YQK[2023]006)the National SKA Program of China(No.2020SKA0110300)the NSFC(No.11963003)the Guizhou Provincial Basic Research Program(Natural Science)(No.ZK[2022]143)the Cultivation project of Guizhou University(No.[2020]76).
文摘Imaging is an important method for astronomy research.In practice,original images acquired by a telescope are often convolved and blurred by the point-spread function(PSF),which is a very unfavorable situation for many scientific studies including astronomy.This paper introduced a single equation iterative method for solving complex linear equations,and this method can deconvolute dirty images,eliminate the effects of the PSF well.With different PSFs,this algorithm shows very good results in deconvolution.Also,with a giant PSF of aperture synthesis imaging,this algorithm improves the peak signal-to-noise ratio and structural similarity of the dirty images by 41.0%and 33.9%on average.In addition,this paper proves that the algorithm can deconvolute the dirty image by making full use of the information of each pixel in the image,even if the dirty image has salt and pepper noise or even lost areas;by its excellent properties of flexible operation to a single pixel,all these bad situations can be dealt with and the image can be restored.
文摘Data hiding methods involve embedding secret messages into cover objects to enable covert communication in a way that is difficult to detect.In data hiding methods based on image interpolation,the image size is reduced and then enlarged through interpolation,followed by the embedding of secret data into the newly generated pixels.A general improving approach for embedding secret messages is proposed.The approach may be regarded a general model for enhancing the data embedding capacity of various existing image interpolation-based data hiding methods.This enhancement is achieved by expanding the range of pixel values available for embedding secret messages,removing the limitations of many existing methods,where the range is restricted to powers of two to facilitate the direct embedding of bit-based messages.This improvement is accomplished through the application of multiple-based number conversion to the secret message data.The method converts the message bits into a multiple-based number and uses an algorithm to embed each digit of this number into an individual pixel,thereby enhancing the message embedding efficiency,as proved by a theorem derived in this study.The proposed improvement method has been tested through experiments on three well-known image interpolation-based data hiding methods.The results show that the proposed method can enhance the three data embedding rates by approximately 14%,13%,and 10%,respectively,create stego-images with good quality,and resist RS steganalysis attacks.These experimental results indicate that the use of the multiple-based number conversion technique to improve the three interpolation-based methods for embedding secret messages increases the number of message bits embedded in the images.For many image interpolation-based data hiding methods,which use power-of-two pixel-value ranges for message embedding,other than the three tested ones,the proposed improvement method is also expected to be effective for enhancing their data embedding capabilities.
基金Supported by the National Key R&D Program of China (No.2023YFC3008100)the National Natural Science Foundation of China (No.U23A2033)
文摘Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(FIR)”method for multi-sourced depth data fusion,and used it to merge the electronic nautical chart dataset(referred to as Chart2014 in this paper)with the global digital elevation dataset(referred to as Globalbath2002 in this paper).Compared to the traditional fusion of two datasets by direct combination and interpolation,the new Grid-DEM formed by FIR can better represent the data characteristics of Chart2014,reduce the calculation difficulty,and be more intuitive,and,the choice of different interpolation methods in FIR and the influence of the“exclusion radius R”parameter were discussed.FIR avoids complex calculations of spatial distances among points from different sources,and instead uses spatial exclusion map to perform one-step screening based on the exclusion radius R,which greatly improved the fusion status of a reliable dataset.The fusion results of different experiments were analyzed statistically with root mean square error and mean relative error,showing that the interpolation methods based on Delaunay triangulation are more suitable for the fusion of nautical chart depth of China,and factors such as the point density distribution of multiple source data,accuracy,interpolation method,and various terrain conditions should be fully considered when selecting the exclusion radius R.
基金supported by the National Key Research and Development Project of China(No.2023YFB3709605)the National Natural Science Foundation of China(No.62073193)the National College Student Innovation Training Program(No.202310422122)。
文摘Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.
基金supported by the National Natural Science Foundation of China(NSFC)under grant No.12233012,the Strategic Priority Research Program of the Chinese Academy of Sciences,grant No.XDB0560102the National Key R&D Program of China 2022YFF0503003(2022YFF0503000)。
文摘The in-flight calibration and performance of the Solar Disk Imager(SDI),which is a pivotal instrument of the LyαSolar Telescope onboard the Advanced Space-based Solar Observatory mission,suggested a much lower spatial resolution than expected.In this paper,we developed the SDI point-spread function(PSF)and Image Bivariate Optimization Algorithm(SPIBOA)to improve the quality of SDI images.The bivariate optimization method smartly combines deep learning with optical system modeling.Despite the lack of information about the real image taken by SDI and the optical system function,this algorithm effectively estimates the PSF of the SDI imaging system directly from a large sample of observational data.We use the estimated PSF to conduct deconvolution correction to observed SDI images,and the resulting images show that the spatial resolution after correction has increased by a factor of more than three with respect to the observed ones.Meanwhile,our method also significantly reduces the inherent noise in the observed SDI images.The SPIBOA has now been successfully integrated into the routine SDI data processing,providing important support for the scientific studies based on the data.The development and application of SPIBOA also paves new ways to identify astronomical telescope systems and enhance observational image quality.Some essential factors and precautions in applying the SPIBOA method are also discussed.
基金supported by the National Natural Science Foundation of China(NSFC,Grant Nos.12063002 and 12163004).
文摘Measuring the transverse velocity field in high-resolution solar images is essential for understanding solar dynamics.This paper introduces an innovative unsupervised deep learning optical flow model designed to calculate the transverse velocity field,addressing the challenges of missing optical flow labels and the limited accuracy of velocity field measurements in high-resolution solar images.The proposed method converts the transverse velocity field computation problem into an optical flow computation problem,using two forward propagations of features to get rid of the reliance on optical flow labels.Additionally,it reduces the impact of the“Brightness Consistency”constraint on optical flow accuracy by identifying and handling optical flow outliers.We apply this method to compute the transverse velocity fields of high-resolution solar image sequences from the Hαand TiO bands,observed by the New Vacuum Solar Telescope.Comparative experiments with several wellestablished optical flow methods,including those based on supervised deep learning models,show that our approach outperforms the comparison methods according to key evaluation metrics such as Residual Map Mean,Residual Map Variance,Cross Correlation,and Structural Similarity Index Measure.Moreover,since optical flow captures the fundamental motion information in image sequences,the proposed method can be applied to a variety of research areas,including solar image registration,sequence alignment,image super-resolution,magnetic field calibration,and solar activity forecasting.The code is available at https://github.com/jackie-willianm/Transverse-Velocity-Field-Measurement-of-Solar-High-Resolution-Images.
基金supported by the National Natural Science Foundation of China(Nos.U22A2034,62177047)High Caliber Foreign Experts Introduction Plan funded by MOST,and Central South University Research Programme of Advanced Interdisciplinary Studies(No.2023QYJC020).
文摘Image captioning has seen significant research efforts over the last decade.The goal is to generate meaningful semantic sentences that describe visual content depicted in photographs and are syntactically accurate.Many real-world applications rely on image captioning,such as helping people with visual impairments to see their surroundings.To formulate a coherent and relevant textual description,computer vision techniques are utilized to comprehend the visual content within an image,followed by natural language processing methods.Numerous approaches and models have been developed to deal with this multifaceted problem.Several models prove to be stateof-the-art solutions in this field.This work offers an exclusive perspective emphasizing the most critical strategies and techniques for enhancing image caption generation.Rather than reviewing all previous image captioning work,we analyze various techniques that significantly improve image caption generation and achieve significant performance improvements,including encompassing image captioning with visual attention methods,exploring semantic information types in captions,and employing multi-caption generation techniques.Further,advancements such as neural architecture search,few-shot learning,multi-phase learning,and cross-modal embedding within image caption networks are examined for their transformative effects.The comprehensive quantitative analysis conducted in this study identifies cutting-edgemethodologies and sheds light on their profound impact,driving forward the forefront of image captioning technology.
基金financially supported by the National Key R&D Program of China(2022YFB3806300)。
文摘The China Space Station Telescope(CSST)is a 2 m three-mirror anastigmat equipped with a Fast Steering Mirror(FSM),which is part of its precision image stabilization system.The FSM is used to compensate for residuals from the previous stage of the image stabilization system.However,a new type of image stabilization residual caused by image rotation and projection distortion is introduced when the FSM performs tip-tilt adjustments,reducing both the image stabilization accuracy and the absolute pointing accuracy of the CSST.In this paper,we propose a scheme to compute the image stabilization residuals across the full field of view(FOV)by using a reference star as the target for stabilization control,which can be utilized for subsequent image position correction.To achieve this,we developed a linear optical model for image point displacement by simplifying an existing image point displacement model and incorporating more readily available parameters.The computational accuracy of the new model is equivalent to that of the original,with computational differences of less than 0.03μm.Based on this linear model,we established a calculation model for image stabilization residuals,including those due to image rotation and projection distortion caused by FSM tip-tilt adjustments.This model provides a theoretical foundation for quantifying such residuals during the image stabilization process.Finally,the results of testing using this scheme are provided.Experimental results demonstrate that within the observation FOV of the CSST,when the FSM tilts by(1″,1″),the maximum absolute value of the image stabilization residuals accounts for 20%of the total image stabilization accuracy requirement.This finding underscores the necessity of computing and correcting these residuals to meet performance requirements.
基金This work was supported by the Russian Science Foundation(Grant No.22-19-00765)at the Perm National Research Polytechnic University.
文摘Creating conditions to implement equilibrium processes of damage accumulation under a predictable scenario enables control over the failure of structural elements in critical states.It improves safety and reduces the probability of catastrophic behavior in case of accidents.Equilibrium damage accumulation in some cases leads to a falling part(called a postcritical stage)on the material’s stress-strain curve.It must be taken into account to assess the strength and deformation limits of composite structures.Digital image correlation method,acoustic emission(AE)signals recording,and optical microscopy were used in this paper to study the deformation and failure processes of an orthogonal-layup composite during tension in various directions to orthotropy axes.An elastic-plastic deformation model was proposed for the composite in a plane stress condition.The evolution of strain fields and neck formation were analyzed.The staging of the postcritical deformation process was described.AE signals obtained during tests were studied;characteristic damage types of a material were defined.The rationality and necessity of polymer composites’postcritical deformation stage taken into account in refined strength analysis of structures were concluded.
基金supported by the National Natural Science Foundation of China (NSFC, Grant No. U1731128)
文摘In the task of classifying massive celestial data,the accurate classification of galaxies,stars,and quasars usually relies on spectral labels.However,spectral data account for only a small fraction of all astronomical observation data,and the target source classification information in vast photometric data has not been accurately measured.To address this,we propose a novel deep learning-based algorithm,YL8C4Net,for the automatic detection and classification of target sources in photometric images.This algorithm combines the YOLOv8 detection network with the Conv4Net classification network.Additionally,we propose a novel magnitude-based labeling method for target source annotation.In the performance evaluation,the YOLOv8 achieves impressive performance with average precision scores of 0.824 for AP@0.5 and 0.795 for AP@0.5:0.95.Meanwhile,the constructed Conv4Net attains an accuracy of 0.8895.Overall,YL8C4Net offers the advantages of fewer parameters,faster processing speed,and higher classification accuracy,making it particularly suitable for large-scale data processing tasks.Furthermore,we employed the YL8C4Net model to conduct target source detection and classification on photometric images from 20 sky regions in SDSS-DR17.As a result,a catalog containing about 9.39 million target source classification results has been preliminarily constructed,thereby providing valuable reference data for astronomical research.
基金supported by the National Key R&D Program of China(grant No.2022YFF0503800)by the National Natural Science Foundation of China(NSFC)(grant No.11427901)+1 种基金by the Strategic Priority Research Program of the Chinese Academy of Sciences(CAS-SPP)(grant No.XDA15320102)by the Youth Innovation Promotion Association(CAS No.2022057)。
文摘The Solar Polar-orbit Observatory(SPO),proposed by Chinese scientists,is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small ellipticity.However,one of the most significant challenges lies in ultra-long-distance data transmission,particularly for the Magnetic and Helioseismic Imager(MHI),which is the most important payload and generates the largest volume of data in SPO.In this paper,we propose a tailored lossless data compression method based on the measurement mode and characteristics of MHI data.The background out of the solar disk is removed to decrease the pixel number of an image under compression.Multiple predictive coding methods are combined to eliminate the redundancy utilizing the correlation(space,spectrum,and polarization)in data set,improving the compression ratio.Experimental results demonstrate that our method achieves an average compression ratio of 3.67.The compression time is also less than the general observation period.The method exhibits strong feasibility and can be easily adapted to MHI.
文摘The task of indoor visual localization, utilizing camera visual information for user pose calculation, was a core component of Augmented Reality (AR) and Simultaneous Localization and Mapping (SLAM). Existing indoor localization technologies generally used scene-specific 3D representations or were trained on specific datasets, making it challenging to balance accuracy and cost when applied to new scenes. Addressing this issue, this paper proposed a universal indoor visual localization method based on efficient image retrieval. Initially, a Multi-Layer Perceptron (MLP) was employed to aggregate features from intermediate layers of a convolutional neural network, obtaining a global representation of the image. This approach ensured accurate and rapid retrieval of reference images. Subsequently, a new mechanism using Random Sample Consensus (RANSAC) was designed to resolve relative pose ambiguity caused by the essential matrix decomposition based on the five-point method. Finally, the absolute pose of the queried user image was computed, thereby achieving indoor user pose estimation. The proposed indoor localization method was characterized by its simplicity, flexibility, and excellent cross-scene generalization. Experimental results demonstrated a positioning error of 0.09 m and 2.14° on the 7Scenes dataset, and 0.15 m and 6.37° on the 12Scenes dataset. These results convincingly illustrated the outstanding performance of the proposed indoor localization method.
基金Supported by the National Basic Research Program of China ("973"Program)(2006CB601201)~~
文摘In high-resolution cone-beam computed tomography （CBCT） using the flat-panel detector, imperfect or defect detector elements cause ring artifacts due to the none-uniformity of their X-ray response. They often disturb the image quality. A dedicated fitting correction method for high-resolution micro-CT is presented. The method converts each elementary X-ray response curve to an average one, and eliminates response inconsistency among pixels. Other factors of the method are discussed, such as the correction factor variability by different sampling frames and nonlinear factors over the whole spectrum. Results show that the noise and artifacts are both reduced in reconstructed images
基金supported by the Young Scientists Fund of the National Natural Science Foundation of China(No.41304082)the Young Scientists Fund of the Natural Science Foundation of Hebei Province(No.D2014403011)the Geological survey project of China Geological Survey(No.12120114090201)
文摘We conducted a study on the numerical calculation and response analysis of a transient electromagnetic field generated by a ground source in geological media. One solution method, the traditional discrete image method, involves complex operation, and its digital filtering algorithm requires a large number of calculations. To solve these problems, we proposed an improved discrete image method, where the following are realized： the real number of the electromagnetic field solution based on the Gaver-Stehfest algorithm for approximate inversion, the exponential approximation of the objective kernel function using the Prony method, the transient electromagnetic field according to discrete image theory, and closed-form solution of the approximate coefficients. To verify the method, we tentatively calculated the transient electromagnetic field in a homogeneous model and compared it with the results obtained from the Hankel transform digital filtering method. The results show that the method has considerable accuracy and good applicability. We then used this method to calculate the transient electromagnetic field generated by a ground magnetic dipole source in a typical geoelectric model and analyzed the horizontal component response of the induced magnetic field obtained from the ＂ground excitation-stratum measurement method. We reached the conclusion that the horizontal component response of a transient field is related to the geoelectric structure, observation time, spatial location, and others. The horizontal component response of the induced magnetic field reflects the eddy current field distribution and its vertical gradient variation. During the detection of abnormal objects, positions with a zero or comparatively large offset were selected for the drill- hole measurements or a comparatively long observation delay was adopted to reduce the influence of the ambient field on the survey results. The discrete image method and forward calculation results in this paper can be used as references for relevant research.
基金The National Natural Science Foundation of China (No.61362001,61102043,61262084,20132BAB211030,20122BAB211015)the Basic Research Program of Shenzhen(No.JC201104220219A)
文摘A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inner-level Bregmanized method devotes to dictionary updating and sparse represention of small overlapping image patches. The introduced constraint of graph regularized sparse coding can capture local image features effectively, and consequently enables accurate reconstruction from highly undersampled partial data. Furthermore, modified sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge within a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can effectively reconstruct images and it outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.
基金partially supported by the NSF grants DMS-1854434,DMS-1952644,DMS-2151235,DMS-2219904,and CAREER 1846690。
文摘In this paper,we design an efficient,multi-stage image segmentation framework that incorporates a weighted difference of anisotropic and isotropic total variation(AITV).The segmentation framework generally consists of two stages:smoothing and thresholding,thus referred to as smoothing-and-thresholding(SaT).In the first stage,a smoothed image is obtained by an AITV-regularized Mumford-Shah(MS)model,which can be solved efficiently by the alternating direction method of multipliers(ADMMs)with a closed-form solution of a proximal operator of the l_(1)-αl_(2) regularizer.The convergence of the ADMM algorithm is analyzed.In the second stage,we threshold the smoothed image by K-means clustering to obtain the final segmentation result.Numerical experiments demonstrate that the proposed segmentation framework is versatile for both grayscale and color images,effcient in producing high-quality segmentation results within a few seconds,and robust to input images that are corrupted with noise,blur,or both.We compare the AITV method with its original convex TV and nonconvex TVP(O<p<1)counterparts,showcasing the qualitative and quantitative advantages of our proposed method.
基金supported by the GHfund A(202302017475)supported by the Foundation for Distinguished Young Scholars of Jiangsu Province(No.BK20140050)+5 种基金the National Natural Science Foundation of China(Nos.11973070,11333008,11273061,11825303,and 11673065)the China Manned Space Project with No.CMS-CSST-2021-A01,CMSCSST-2021-A03,CMS-CSST-2021-B01the Joint Funds of the National Natural Science Foundation of China(No.U1931210)the support from Key Research Program of Frontier Sciences,CAS,grant No.ZDBS-LY-7013Program of Shanghai Academic/Technology Research Leaderthe support from the science research grants from the China Manned Space Project with CMS-CSST-2021-A04,CMS-CSST-2021-A07。
文摘We have developed a novel method for co-adding multiple under-sampled images that combines the iteratively reweighted least squares and divide-and-conquer algorithms.Our approach not only allows for the anti-aliasing of the images but also enables Point-Spread Function(PSF)deconvolution,resulting in enhanced restoration of extended sources,the highest peak signal-to-noise ratio,and reduced ringing artefacts.To test our method,we conducted numerical simulations that replicated observation runs of the China Space Station Telescope/the VLT Survey Telescope(VST)and compared our results to those obtained using previous algorithms.The simulation showed that our method outperforms previous approaches in several ways,such as restoring the profile of extended sources and minimizing ringing artefacts.Additionally,because our method relies on the inherent advantages of least squares fitting,it is more versatile and does not depend on the local uniformity hypothesis for the PSF.However,the new method consumes much more computation than the other approaches.
基金supported by the China Geological Survey (No.1212011014030)the Major State Basic Research Development Program of China (973 Program) (No.2011CB710600)
文摘The estimation of shear strength of rock mass discontinuity is always a focal, but difficult, problem in the field of geotechnical engineering. Considering the disadvantages and limitation of exist- ing estimation methods, a new approach based on the shadow area percentage （SAP） that can be used to quantify surface roughness is proposed in this article. Firstly, by the help of laser scanning technique, the three-dimensional model of the surface of rock discontinuity was established. Secondly, a light source was simulated, and there would be some shadows produced on the model surface. Thirdly, to obtain the value of SAP of each specimen, the shadow detection technique was introduced for use. Fourthly, compared with the result from direct shear testing and based on statistics, an empirical for- mula was found among SAP, normal stress, and shear strength. Data of Yujian （~ River were used as an example, and the following conclusions have been made. （1） In the case of equal normal stress, the peak shear stress is positively proportional to the SAP. （2） The formula for estimating was derived, and the predictions of peak-shear strength made with this equation well agreed with the experimental re- suits obtained in laboratory tests.
基金Supported by the National Basic Research Program ofChina(2011CB707900)
文摘To segment the tumor region precisely is a prerequisite for ultrasound navigation and treatment. In this paper, a normalized cut method to segment tumor ultrasound image is proposed by means of simple linear iterative clustering for presegmentation procedure. The first step, we use simple linear iterative clustering algorithm to divide the image into a number of homogeneous over-segmented regions. Then, these regions are regarded as nodes, and a similarity matrix is constructed by comparing the histograms of each two regions. Finally, we apply the Ncut method to merging the over-segmented regions, then the image segmentation process is completed. The results show that the proposed segmentation scheme handles the strong speckle noise, low contrast, and weak edges well in ultrasound image. Our method has high segmentation precision and computation efficiency than the pixel-based Ncut method.
