With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-...With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.展开更多
Using the Radon transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gra...Using the Radon transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gray-level and binary images, the linear texture of ship wake in oceanic clutter can be well detected. It has been applied to the automatic detection of a moving ship from the SEASAT SAR image. The results show that this algorithm is well robust in a strong noisy background and is not very sensitive to the threshold parameter and the working window size.展开更多
An effective processing method for biomedical images and the Fuzzy C-mean (FCM) algorithm based on the wavelet transform are investigated.By using hierarchical wavelet decomposition, an original image could be decompo...An effective processing method for biomedical images and the Fuzzy C-mean (FCM) algorithm based on the wavelet transform are investigated.By using hierarchical wavelet decomposition, an original image could be decomposed into one lower image and several detail images. The segmentation started at the lowest resolution with the FCM clustering algorithm and the texture feature extracted from various sub-bands. With the improvement of the FCM algorithm, FCM alternation frequency was decreased and the accuracy of segmentation was advanced.展开更多
In order to obtain good welding quality, it is necessary to apply quality control because there are many influencing factors in laser welding process. The key to realize welding quality control is to obtain the qualit...In order to obtain good welding quality, it is necessary to apply quality control because there are many influencing factors in laser welding process. The key to realize welding quality control is to obtain the quality information. Abundant weld quality information is contained in weld pool and keyhole. Aiming at Nd：YAG laser welding of stainless steel, a coaxial visual sensing system was constructed. The images of weld pool and keyhole were obtained. Based on the gray character of weld pool and keyhole in images, an image processing algorithm was designed. The search start point and search criteria of weld pool and keyhole edge were determined respectively.展开更多
With the rapid development of sports,the number of sports images has increased dramatically.Intelligent and automatic processing and analysis of moving images are significant,which can not only facilitate users to qui...With the rapid development of sports,the number of sports images has increased dramatically.Intelligent and automatic processing and analysis of moving images are significant,which can not only facilitate users to quickly search and access moving images but also facilitate staff to store and manage moving image data and contribute to the intellectual development of the sports industry.In this paper,a method of table tennis identification and positioning based on a convolutional neural network is proposed,which solves the problem that the identification and positioning method based on color features and contour features is not adaptable in various environments.At the same time,the learning methods and techniques of table tennis detection,positioning,and trajectory prediction are studied.A deep learning framework for recognition learning of rotating flying table tennis is put forward.The mechanism and methods of positioning,trajectory prediction,and intelligent automatic processing of moving images are studied,and the self-built data sets are trained and verified.展开更多
The paper presents the implementation of a parallel version of FDK （Felkamp, David e Kress） algorithm using graphics processing units. Discussion was briefly some elements the computed tomographic scan and FDK algor...The paper presents the implementation of a parallel version of FDK （Felkamp, David e Kress） algorithm using graphics processing units. Discussion was briefly some elements the computed tomographic scan and FDK algorithm; and some ideas about GPUs （Graphics Processing Units） and its use in general purpose computing were presented. The paper shows a computational implementation of FDK algorithm and the process of parallelization of this implementation. Compare the parallel version of the algorithm with the sequential version, used speedup as a performance metric. To evaluate the performance of parallel version, two GPUs, GeForce 9400GT （16 cores） a low capacity GPU and Quadro 2000 （192 cores） a medium capacity GPU was reached speedup of 3.37.展开更多
A numerical algorithm of principal component analysis (PCA) is proposed and its application in remote sensing image processing is introduced: (1) Multispectral image compression;(2) Multi-spectral image noise cancella...A numerical algorithm of principal component analysis (PCA) is proposed and its application in remote sensing image processing is introduced: (1) Multispectral image compression;(2) Multi-spectral image noise cancellation;(3) Information fusion of multi-spectral images and spot panchromatic images. The software experiments verify and evaluate the effectiveness and accuracy of the proposed algorithm.展开更多
We investigated image processing algorithms of the original infrared glass flaw image. Using the Laplacian edge enhancement following LSD （Line Segment Detector） algorithm, we can get a good flaw image very consiste...We investigated image processing algorithms of the original infrared glass flaw image. Using the Laplacian edge enhancement following LSD （Line Segment Detector） algorithm, we can get a good flaw image very consistent with the original one. This study is very helpful to further enhance the infrared glass flaw inspection technique.展开更多
To improve image processing speed and detection precision of a surface detection system on a strip surface,based on the analysis of the characteristics of image data and image processing in detection system on the str...To improve image processing speed and detection precision of a surface detection system on a strip surface,based on the analysis of the characteristics of image data and image processing in detection system on the strip surface,the design of parallel image processing system and the methods of algorithm implementation have been studied. By using field programmable gate array(FPGA) as hardware platform of implementation and considering the characteristic of detection system on the strip surface,a parallel image processing system implemented by using multi IP kernel is designed. According to different computing tasks and the load balancing capability of parallel processing system,the system could set different calculating numbers of nodes to meet the system's demand and save the hardware cost.展开更多
Laser welding is one of high efficiency, high energy density welding methods. Quality control should be applied to ensure good welding quality. Weld pool and keyhole contains abundant information of welding quality. G...Laser welding is one of high efficiency, high energy density welding methods. Quality control should be applied to ensure good welding quality. Weld pool and keyhole contains abundant information of welding quality. Good image processing algorithm is necessary in quality control system based on visual sensing. Aiming at the image captured by a coaxial visual sensing system for laser welding, an image processing algorithm is designed. An edge predicting method is proposed in image processing algorithm which is based on the fact that the local shape of weld pool can be fitted to a circle. The results show that the algorithm works well. It lays solid foundation for further quality control in laser welding.展开更多
Angle detection is a crucial aspect of industrial automation,ensuring precise alignment and orientation ofcomponents in manufacturing processes.Despite the widespread application of computer vision in industrialsettin...Angle detection is a crucial aspect of industrial automation,ensuring precise alignment and orientation ofcomponents in manufacturing processes.Despite the widespread application of computer vision in industrialsettings,angle detection remains an underexplored domain,with limited integration into production lines.Thispaper addresses the need for automated angle detection in industrial environments by presenting a methodologythat eliminates training time and higher computation cost on Graphics Processing Unit(GPU)from machinelearning in computer vision(e.g.,Convolutional Neural Networks(CNN)).Our approach leverages advanced imageprocessing techniques and a strategic combination of algorithms,including contour selection,circle regression,polar warp transformation,and outlier detection,to provide an adaptive solution for angle detection.By configuringthe algorithm with a diverse dataset and evaluating its performance across various objects,we demonstrate itsefficacy in achieving reliable results,with an average error of only 0.5 degrees.Notably,this error margin is 3.274times lower than the acceptable threshold.Our study highlights the importance of accurate angle detection inindustrial settings and showcases the reliability of our algorithm in accurately determining angles,thus contributingto improved manufacturing processes.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 quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition...The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition can be influenced.For addressing this issue,a method for extracting ship targets with overlaps via the expectation maximization(EM)algorithm is pro-posed.First,the scatterers of ship targets are obtained via the target detection technique.Then,the EM algorithm is applied to extract the scatterers of a single ship target with a single IPP.Afterwards,a novel image amplitude estimation approach is pro-posed,with which the radar image of a single target with a sin-gle IPP can be generated.The proposed method can accom-plish IPP selection and targets separation in the image domain,which can improve the image quality and reserve the target information most possibly.Results of simulated and real mea-sured data demonstrate the effectiveness of the proposed method.展开更多
The remote sensing image classification has stimulated considerable interest as an effective method for better retrieving information from the rapidly increasing large volume, complex and distributed satellite remote ...The remote sensing image classification has stimulated considerable interest as an effective method for better retrieving information from the rapidly increasing large volume, complex and distributed satellite remote imaging data of large scale and cross-time, due to the increase of remote image quantities and image resolutions. In the paper, the genetic algorithms were employed to solve the weighting of the radial basis faction networks in order to improve the precision of remote sensing image classification. The remote sensing image classification was also introduced for the GIS spatial analysis and the spatial online analytical processing (OLAP), and the resulted effectiveness was demonstrated in the analysis of land utilization variation of Daqing city.展开更多
In this paper, the authors propose a new algorithm to hide data inside image using steganography technique. The proposed algorithm uses binary codes and pixels inside an image. The zipped file is used before it is con...In this paper, the authors propose a new algorithm to hide data inside image using steganography technique. The proposed algorithm uses binary codes and pixels inside an image. The zipped file is used before it is converted to binary codes to maximize the storage of data inside the image. By applying the proposed algorithm, a system called Steganography Imaging System （gig） is developed. The system is then tested to see the viability of the proposed algorithm. Various sizes of data are stored inside the images and the Peak signal-to-noise ratio （PSNR） is also captured for each of the images tested. Based on the PSNR value of each images, the stego image has a higher PSNR value. Hence this new steganography algorithm is very efficient to hide the data inside the image.展开更多
Traditional cameras inevitably suffer from motion blur when facing high-speed moving objects.Event cameras,as high temporal resolution bionic cameras,record intensity changes in an asynchronous manner,and their record...Traditional cameras inevitably suffer from motion blur when facing high-speed moving objects.Event cameras,as high temporal resolution bionic cameras,record intensity changes in an asynchronous manner,and their recorded high temporal resolution information can effectively solve the problem of time information loss in motion blur.Existing event-based deblurring methods still face challenges when facing high-speed moving objects.We conducted an in-depth study of the imaging principle of event cameras.We found that the event stream contains excessive noise.The valid information is sparse.Invalid event features hinder the expression of valid features due to the uncertainty of the global threshold.To address this problem,a denoising-based long and short-term memory module(DTM)is designed in this paper.The DTM suppressed the original event information by noise reduction process.Invalid features in the event stream and solves the problem of sparse valid information in the event stream,and it also combines with the long short-term memory module(LSTM),which further enhances the event feature information in the time scale.In addition,through the in-depth understanding of the unique characteristics of event features,it is found that the high-frequency information recorded by event features does not effectively guide the fusion feature deblurring process in the spatial-domain-based feature processing,and for this reason,we introduce the residual fast fourier transform module(RES-FFT)to further enhance the high-frequency characteristics of the fusion features by performing the feature extraction of the fusion features from the perspective of the frequency domain.Ultimately,our proposed event image fusion network based on event denoising and frequency domain feature enhancement(DNEFNET)achieved Peak Signal-to-Noise Ratio(PSNR)/Structural Similarity Index Measure(SSIM)scores of 35.55/0.972 on the GoPro dataset and 38.27/0.975 on the REBlur dataset,achieving the state of the art(SOTA)effect.展开更多
The integrated circuit chip with high performance has a high sensitivity to the defects in manufacturing environments.When there are defects on a wafer,the defects may lead to the degradation of chip performance.It is...The integrated circuit chip with high performance has a high sensitivity to the defects in manufacturing environments.When there are defects on a wafer,the defects may lead to the degradation of chip performance.It is necessary to design effective detection approaches for the defects in order to ensure the reliability of wafer.In this paper,a new method based on image boundary extraction is presented for the detection of defects on a wafer.The method uses island model genetic algorithms to perform the segmentation of wafer images,and gets the optimal threshold values.The island model genetic algorithm uses two distinct subpopulations,it is a coarse grain parallel model.The individuals migration can occur between the two subpopulations to share genetic materials.A lot of experimental results show that the defect detection method proposed in this paper can obtain the features of defects effectively.展开更多
In this paper,a multirate processing approach for microwave imaging is presented.This approach has the advantages of largely compressing the raw spectral data for imaging,greatly reducing the storage requirement and e...In this paper,a multirate processing approach for microwave imaging is presented.This approach has the advantages of largely compressing the raw spectral data for imaging,greatly reducing the storage requirement and enhancing the processing efficiency.To demonstrateits applicability,the proposed approach is tested on both simulated and experimental data.展开更多
Genetic algorithm is a search algorithm based on genetic mechanism and natural selection. It has been widely applied to research fields including image processing field. The paper improves standard genetic algorithm a...Genetic algorithm is a search algorithm based on genetic mechanism and natural selection. It has been widely applied to research fields including image processing field. The paper improves standard genetic algorithm and improves the arithmetic speed of the algorithm, which achieves better image restoration effect. And the paper compares the image restoration quality of traditional algorithm, standard genetic algorithm and improved genetic algorithm to prove the feasibility of applying genetic algorithm to image restoration.展开更多
In the roughing process of hot continuous rolling, due to the lack of detection and control means of intermediate billet warpage, the problem of intermediate billet warpage is always one of the difficult problems in i...In the roughing process of hot continuous rolling, due to the lack of detection and control means of intermediate billet warpage, the problem of intermediate billet warpage is always one of the difficult problems in iron and steel enterprises. Although the machine vision based warping detection method in a factory can obtain effective warping data, it still has the disadvantages of long image processing time and poor timeliness. Therefore, this paper proposes a light stripe image processing algorithm based on dual ROI, which optimizes the line structured light image processing method, greatly improves the algorithm speed and ensures the real-time performance of warping detection system. At the same time, in order to improve the stability of the line structured light image processing, combined with the characteristics of the image, a threshold processing algorithm based on the percentage of the gray peak value of the light stripe is proposed to ensure the high-quality image of the light stripe area.展开更多
基金supported in part by the Technical Service for the Development and Application of an Intelligent Visual Management Platformfor Expressway Construction Progress Based on BIM Technology(grant NO.JKYZLX-2023-09)in partby the Technical Service for the Development of an Early Warning Model in the Research and Application of Key Technologies for Tunnel Operation Safety Monitoring and Early Warning Based on Digital Twin(grant NO.JK-S02-ZNGS-202412-JISHU-FA-0035)sponsored by Yunnan Transportation Science Research Institute Co.,Ltd.
文摘With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.
基金This project was supported by the National Natural Science Foundation of China (No. 49831060).
文摘Using the Radon transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gray-level and binary images, the linear texture of ship wake in oceanic clutter can be well detected. It has been applied to the automatic detection of a moving ship from the SEASAT SAR image. The results show that this algorithm is well robust in a strong noisy background and is not very sensitive to the threshold parameter and the working window size.
文摘An effective processing method for biomedical images and the Fuzzy C-mean (FCM) algorithm based on the wavelet transform are investigated.By using hierarchical wavelet decomposition, an original image could be decomposed into one lower image and several detail images. The segmentation started at the lowest resolution with the FCM clustering algorithm and the texture feature extracted from various sub-bands. With the improvement of the FCM algorithm, FCM alternation frequency was decreased and the accuracy of segmentation was advanced.
基金Project (10776020) supported by the Joint Foundation of the National Natural Science Foundation of China and China Academy of Engineering Physics
文摘In order to obtain good welding quality, it is necessary to apply quality control because there are many influencing factors in laser welding process. The key to realize welding quality control is to obtain the quality information. Abundant weld quality information is contained in weld pool and keyhole. Aiming at Nd：YAG laser welding of stainless steel, a coaxial visual sensing system was constructed. The images of weld pool and keyhole were obtained. Based on the gray character of weld pool and keyhole in images, an image processing algorithm was designed. The search start point and search criteria of weld pool and keyhole edge were determined respectively.
文摘With the rapid development of sports,the number of sports images has increased dramatically.Intelligent and automatic processing and analysis of moving images are significant,which can not only facilitate users to quickly search and access moving images but also facilitate staff to store and manage moving image data and contribute to the intellectual development of the sports industry.In this paper,a method of table tennis identification and positioning based on a convolutional neural network is proposed,which solves the problem that the identification and positioning method based on color features and contour features is not adaptable in various environments.At the same time,the learning methods and techniques of table tennis detection,positioning,and trajectory prediction are studied.A deep learning framework for recognition learning of rotating flying table tennis is put forward.The mechanism and methods of positioning,trajectory prediction,and intelligent automatic processing of moving images are studied,and the self-built data sets are trained and verified.
文摘The paper presents the implementation of a parallel version of FDK （Felkamp, David e Kress） algorithm using graphics processing units. Discussion was briefly some elements the computed tomographic scan and FDK algorithm; and some ideas about GPUs （Graphics Processing Units） and its use in general purpose computing were presented. The paper shows a computational implementation of FDK algorithm and the process of parallelization of this implementation. Compare the parallel version of the algorithm with the sequential version, used speedup as a performance metric. To evaluate the performance of parallel version, two GPUs, GeForce 9400GT （16 cores） a low capacity GPU and Quadro 2000 （192 cores） a medium capacity GPU was reached speedup of 3.37.
文摘A numerical algorithm of principal component analysis (PCA) is proposed and its application in remote sensing image processing is introduced: (1) Multispectral image compression;(2) Multi-spectral image noise cancellation;(3) Information fusion of multi-spectral images and spot panchromatic images. The software experiments verify and evaluate the effectiveness and accuracy of the proposed algorithm.
基金Funded by the Program for New Century Excellent Talents in University (11-0687)the National Natural Science Foundation of China (51172169)the Fundamental Research Funds for the Central Universities (Wuhan University of Technology)
文摘We investigated image processing algorithms of the original infrared glass flaw image. Using the Laplacian edge enhancement following LSD （Line Segment Detector） algorithm, we can get a good flaw image very consistent with the original one. This study is very helpful to further enhance the infrared glass flaw inspection technique.
基金The 111 project(B07018) Supported by Program for Changjiang Scholars and Innovative Research Teamin University(IRT0423)
文摘To improve image processing speed and detection precision of a surface detection system on a strip surface,based on the analysis of the characteristics of image data and image processing in detection system on the strip surface,the design of parallel image processing system and the methods of algorithm implementation have been studied. By using field programmable gate array(FPGA) as hardware platform of implementation and considering the characteristic of detection system on the strip surface,a parallel image processing system implemented by using multi IP kernel is designed. According to different computing tasks and the load balancing capability of parallel processing system,the system could set different calculating numbers of nodes to meet the system's demand and save the hardware cost.
文摘Laser welding is one of high efficiency, high energy density welding methods. Quality control should be applied to ensure good welding quality. Weld pool and keyhole contains abundant information of welding quality. Good image processing algorithm is necessary in quality control system based on visual sensing. Aiming at the image captured by a coaxial visual sensing system for laser welding, an image processing algorithm is designed. An edge predicting method is proposed in image processing algorithm which is based on the fact that the local shape of weld pool can be fitted to a circle. The results show that the algorithm works well. It lays solid foundation for further quality control in laser welding.
文摘Angle detection is a crucial aspect of industrial automation,ensuring precise alignment and orientation ofcomponents in manufacturing processes.Despite the widespread application of computer vision in industrialsettings,angle detection remains an underexplored domain,with limited integration into production lines.Thispaper addresses the need for automated angle detection in industrial environments by presenting a methodologythat eliminates training time and higher computation cost on Graphics Processing Unit(GPU)from machinelearning in computer vision(e.g.,Convolutional Neural Networks(CNN)).Our approach leverages advanced imageprocessing techniques and a strategic combination of algorithms,including contour selection,circle regression,polar warp transformation,and outlier detection,to provide an adaptive solution for angle detection.By configuringthe algorithm with a diverse dataset and evaluating its performance across various objects,we demonstrate itsefficacy in achieving reliable results,with an average error of only 0.5 degrees.Notably,this error margin is 3.274times lower than the acceptable threshold.Our study highlights the importance of accurate angle detection inindustrial settings and showcases the reliability of our algorithm in accurately determining angles,thus contributingto improved manufacturing processes.
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This work was supported by the National Science Fund for Distinguished Young Scholars(62325104).
文摘The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition can be influenced.For addressing this issue,a method for extracting ship targets with overlaps via the expectation maximization(EM)algorithm is pro-posed.First,the scatterers of ship targets are obtained via the target detection technique.Then,the EM algorithm is applied to extract the scatterers of a single ship target with a single IPP.Afterwards,a novel image amplitude estimation approach is pro-posed,with which the radar image of a single target with a sin-gle IPP can be generated.The proposed method can accom-plish IPP selection and targets separation in the image domain,which can improve the image quality and reserve the target information most possibly.Results of simulated and real mea-sured data demonstrate the effectiveness of the proposed method.
基金Sponsored by the National Natural Science Foundation of China (Grant No.40271044), Natural Science Foundation(Grant No.TK2005 -17) and Projectof Science Backbone of Heilongjiang Province(Grant No.1151G021).
文摘The remote sensing image classification has stimulated considerable interest as an effective method for better retrieving information from the rapidly increasing large volume, complex and distributed satellite remote imaging data of large scale and cross-time, due to the increase of remote image quantities and image resolutions. In the paper, the genetic algorithms were employed to solve the weighting of the radial basis faction networks in order to improve the precision of remote sensing image classification. The remote sensing image classification was also introduced for the GIS spatial analysis and the spatial online analytical processing (OLAP), and the resulted effectiveness was demonstrated in the analysis of land utilization variation of Daqing city.
文摘In this paper, the authors propose a new algorithm to hide data inside image using steganography technique. The proposed algorithm uses binary codes and pixels inside an image. The zipped file is used before it is converted to binary codes to maximize the storage of data inside the image. By applying the proposed algorithm, a system called Steganography Imaging System （gig） is developed. The system is then tested to see the viability of the proposed algorithm. Various sizes of data are stored inside the images and the Peak signal-to-noise ratio （PSNR） is also captured for each of the images tested. Based on the PSNR value of each images, the stego image has a higher PSNR value. Hence this new steganography algorithm is very efficient to hide the data inside the image.
文摘Traditional cameras inevitably suffer from motion blur when facing high-speed moving objects.Event cameras,as high temporal resolution bionic cameras,record intensity changes in an asynchronous manner,and their recorded high temporal resolution information can effectively solve the problem of time information loss in motion blur.Existing event-based deblurring methods still face challenges when facing high-speed moving objects.We conducted an in-depth study of the imaging principle of event cameras.We found that the event stream contains excessive noise.The valid information is sparse.Invalid event features hinder the expression of valid features due to the uncertainty of the global threshold.To address this problem,a denoising-based long and short-term memory module(DTM)is designed in this paper.The DTM suppressed the original event information by noise reduction process.Invalid features in the event stream and solves the problem of sparse valid information in the event stream,and it also combines with the long short-term memory module(LSTM),which further enhances the event feature information in the time scale.In addition,through the in-depth understanding of the unique characteristics of event features,it is found that the high-frequency information recorded by event features does not effectively guide the fusion feature deblurring process in the spatial-domain-based feature processing,and for this reason,we introduce the residual fast fourier transform module(RES-FFT)to further enhance the high-frequency characteristics of the fusion features by performing the feature extraction of the fusion features from the perspective of the frequency domain.Ultimately,our proposed event image fusion network based on event denoising and frequency domain feature enhancement(DNEFNET)achieved Peak Signal-to-Noise Ratio(PSNR)/Structural Similarity Index Measure(SSIM)scores of 35.55/0.972 on the GoPro dataset and 38.27/0.975 on the REBlur dataset,achieving the state of the art(SOTA)effect.
基金supported by Guangdong Provincial Natural Science Foundation of China (7005833)
文摘The integrated circuit chip with high performance has a high sensitivity to the defects in manufacturing environments.When there are defects on a wafer,the defects may lead to the degradation of chip performance.It is necessary to design effective detection approaches for the defects in order to ensure the reliability of wafer.In this paper,a new method based on image boundary extraction is presented for the detection of defects on a wafer.The method uses island model genetic algorithms to perform the segmentation of wafer images,and gets the optimal threshold values.The island model genetic algorithm uses two distinct subpopulations,it is a coarse grain parallel model.The individuals migration can occur between the two subpopulations to share genetic materials.A lot of experimental results show that the defect detection method proposed in this paper can obtain the features of defects effectively.
文摘In this paper,a multirate processing approach for microwave imaging is presented.This approach has the advantages of largely compressing the raw spectral data for imaging,greatly reducing the storage requirement and enhancing the processing efficiency.To demonstrateits applicability,the proposed approach is tested on both simulated and experimental data.
文摘Genetic algorithm is a search algorithm based on genetic mechanism and natural selection. It has been widely applied to research fields including image processing field. The paper improves standard genetic algorithm and improves the arithmetic speed of the algorithm, which achieves better image restoration effect. And the paper compares the image restoration quality of traditional algorithm, standard genetic algorithm and improved genetic algorithm to prove the feasibility of applying genetic algorithm to image restoration.
文摘In the roughing process of hot continuous rolling, due to the lack of detection and control means of intermediate billet warpage, the problem of intermediate billet warpage is always one of the difficult problems in iron and steel enterprises. Although the machine vision based warping detection method in a factory can obtain effective warping data, it still has the disadvantages of long image processing time and poor timeliness. Therefore, this paper proposes a light stripe image processing algorithm based on dual ROI, which optimizes the line structured light image processing method, greatly improves the algorithm speed and ensures the real-time performance of warping detection system. At the same time, in order to improve the stability of the line structured light image processing, combined with the characteristics of the image, a threshold processing algorithm based on the percentage of the gray peak value of the light stripe is proposed to ensure the high-quality image of the light stripe area.
