Lunar Laser Ranging has extremely high requirements for the pointing accuracy of the telescopes used.To improve its pointing accuracy and solve the problem of insufficiently accurate telescope pointing correction achi...Lunar Laser Ranging has extremely high requirements for the pointing accuracy of the telescopes used.To improve its pointing accuracy and solve the problem of insufficiently accurate telescope pointing correction achieved by tracking stars in the all-sky region,we propose a processing scheme to select larger-sized lunar craters near the Lunar Corner Cube Retroreflector as reference features for telescope pointing bias computation.Accurately determining the position of the craters in the images is crucial for calculating the pointing bias;therefore,we propose a method for accurately calculating the crater position based on lunar surface feature matching.This method uses matched feature points obtained from image feature matching,using a deep learning method to solve the image transformation matrix.The known position of a crater in a reference image is mapped using this matrix to calculate the crater position in the target image.We validate this method using craters near the Lunar Corner Cube Retroreflectors of Apollo 15 and Luna 17 and find that the calculated position of a crater on the target image falls on the center of the crater,even for image features with large distortion near the lunar limb.The maximum image matching error is approximately 1″,and the minimum is only 0.47″,which meets the pointing requirements of Lunar Laser Ranging.This method provides a new technical means for the high-precision pointing bias calculation of the Lunar Laser Ranging system.展开更多
Choosing appropriate background field data is crucial for gravity field matching navigation.Current research mainly uses gravity anomaly data or gravity gradient data as background fields.However,using gravity gradien...Choosing appropriate background field data is crucial for gravity field matching navigation.Current research mainly uses gravity anomaly data or gravity gradient data as background fields.However,using gravity gradient invariants in existing research is seldom a concern.The gravity gradient tensor has three invariants,named as I_(1),I_(2)and I_(3).I_(1) is a Laplace operator outside the Earth and a Poison operator inside the Earth.The focus of this study is to discuss the performance of the other two invariants of gravity gradients in matching navigation based on the Iterative Closest Contour Point(ICCP)algorithm and compare the matching results with that of the gravity gradient Tzz.The results show that they have almost the same performance when there is no noise,and the background data noises have a large impact on the matching results.There are differences in the anti-interference ability of observation noises for the different components.Under the same random noises in the observations,I2performs a little better than the other two components in terms of position error standard deviation.According to the investigations,since attitude errors can not be avoided and influence the positioning based on Tzz,we recommend adopting invariants of gravity gradients,especially I2,for matching navigation in actual cases.展开更多
Based on the coded and non-coded targets, the targets are extracted from the images according to their size, shape and intensity etc., and thus an improved method to identify the unique identity（D） of every coded ta...Based on the coded and non-coded targets, the targets are extracted from the images according to their size, shape and intensity etc., and thus an improved method to identify the unique identity（D） of every coded target is put forward and the non-coded and coded targets are classified. Moreover, the gray scale centroid algorithm is applied to obtain the subpixel location of both uncoded and coded targets. The initial matching of the uncoded target correspondences between an image pair is established according to similarity and compatibility, which are based on the ID correspondences of the coded targets. The outliers in the initial matching of the uncoded target are eliminated according to three rules to finally obtain the uncoded target correspondences. Practical examples show that the algorithm is rapid, robust and is of high precision and matching ratio.展开更多
Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topologi...Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topological Characteristics (PPTC) and Spectral Matching (SM) together to solve the afore mentioned issues. In which PPTC, a new shape descriptor, is firstly proposed. A new comparability measurement based on PPTC is defined as the matching probability. Finally, the correct matching results are achieved by the spectral matching method. The synthetic data experiments show its robustness by comparing with the other state-of-art algorithms and the real world data experiments show its effectiveness.展开更多
Non-rigid point matching has received more and more attention.Recently,many works have been developed to discover global relationships in the point set which is treated as an instance of a joint distribution.However,t...Non-rigid point matching has received more and more attention.Recently,many works have been developed to discover global relationships in the point set which is treated as an instance of a joint distribution.However,the local relationship among neighboring points is more effective under non-rigid transformations.Thus,a new algorithm taking advantage of shape context and relaxation labeling technique,called SC-RL,is proposed for non-rigid point matching.It is a strategy that joints estimation for correspondences as well as the transformation.In this work,correspondence assignment is treated as a soft-assign process in which the matching probability is updated by relaxation labeling technique with a newly defined compatibility coefficient.The compatibility coefficient is one or zero depending on whether neighboring points preserving their relative position in a local coordinate system.The comparative analysis has been performed against four state-of-the-art algorithms including SC,ICP,TPS-RPM and RPM-LNS,and the results denote that SC-RL performs better in the presence of deformations,outliers and noise.展开更多
In photogrammetry and remote sensing,image matching is a basic and crucial process for automatic DEM generation.In this paper we presented a image relaxation matching method based on feature points.This method can be ...In photogrammetry and remote sensing,image matching is a basic and crucial process for automatic DEM generation.In this paper we presented a image relaxation matching method based on feature points.This method can be considered as an extention of regular grid point based matching.It avoids the shortcome of grid point based matching.For example,with this method,we can avoid low or even no texture area where errors frequently appear in cross correlaton matching.In the mean while,it makes full use of some mature techniques such as probability relaxation,image pyramid and the like which have already been successfully used in grid point matching process.Application of the technique to DEM generaton in different regions proved that it is more reasonable and reliable.展开更多
A novel tie point matching algorithm of aerial images with the assistance of airborne LiDAR point clouds and POS data is proposed Firstly,the conjugate point searching strategy used in traditional correlation coeffici...A novel tie point matching algorithm of aerial images with the assistance of airborne LiDAR point clouds and POS data is proposed Firstly,the conjugate point searching strategy used in traditional correlation coefficient matching is improved and a fast algorithm is presented.Secondly,an automatic camera boresight misalignment calibration method based on virtual ground control points is proposed,and then the searching range of image matching is adaptively determined and applied to the image matching of the entire surveying area.Test results verified that the fast correlation coefficient matching algorithm proposed in this paper can reduce approximately 25% of the matching time without the loss of matching accuracy.The camera boresight misalignment calibration method can effectively increase the accuracy of exterior orientation elements of images calculated from POS data,and thus can significantly improve the predicted position of conjugate point for tie point matching.Our proposed image matching algorithm can achieve superior matching accuracy with multi-scale,multi-view,and cross-flight aerial images.展开更多
A coding-based method to solve the image matching problems in stereovision measurement is presented. The solution is to add and append an identity ID to the retro-reflect point, so it can be identified efficiently und...A coding-based method to solve the image matching problems in stereovision measurement is presented. The solution is to add and append an identity ID to the retro-reflect point, so it can be identified efficiently under the complicated circumstances and has the characteristics of rotation, zooming, and deformation independence. Its design architecture and implementation process in details based on the theory of stereovision measurement are described. The method is effective on reducing processing data time, improving accuracy of image matching and automation of measuring system through experiments.展开更多
In this article, a Ky Fan matching theorem for transfer compactly open covers is established. As applications, a Fan-Browder coincidence theorem, a Ky Fan best approximation theorem and a Brouwer-Schauder-Rothe type f...In this article, a Ky Fan matching theorem for transfer compactly open covers is established. As applications, a Fan-Browder coincidence theorem, a Ky Fan best approximation theorem and a Brouwer-Schauder-Rothe type fixed point theorem are obtained.展开更多
To improve the performance of the scale invariant feature transform （ SIFT）, a modified SIFT （M-SIFT） descriptor is proposed to realize fast and robust key-point extraction and matching. In descriptor generation, ...To improve the performance of the scale invariant feature transform （ SIFT）, a modified SIFT （M-SIFT） descriptor is proposed to realize fast and robust key-point extraction and matching. In descriptor generation, 3 rotation-invariant concentric-ring grids around the key-point location are used instead of 16 square grids used in the original SIFT. Then, 10 orientations are accumulated for each grid, which results in a 30-dimension descriptor. In descriptor matching, rough rejection mismatches is proposed based on the difference of grey information between matching points. The per- formance of the proposed method is tested for image mosaic on simulated and real-worid images. Experimental results show that the M-SIFT descriptor inherits the SIFT＇ s ability of being invariant to image scale and rotation, illumination change and affine distortion. Besides the time cost of feature extraction is reduced by 50% compared with the original SIFT. And the rough rejection mismatches can reject at least 70% of mismatches. The results also demonstrate that the performance of the pro- posed M-SIFT method is superior to other improved SIFT methods in speed and robustness.展开更多
During matching on feature point, gray correlation matching technology is utilized to extract multi-peaks as a coarse matching set. A pair of given corresponding reference points within the left and right images is us...During matching on feature point, gray correlation matching technology is utilized to extract multi-peaks as a coarse matching set. A pair of given corresponding reference points within the left and right images is used to calculate gradients of reference difference between the reference points and each feature point within the multi-peaks set. The unique correspondence is determined by criterion of minimal gradients of reference difference. The obtained correspondence is taken as a new pair of reference points to update the reference points continuously until all feature points in the left (or right) image being matched with the right (or left) image. The gradients of reference difference can be calculated easily by means of pre-setting a pair of obvious feature points in the left and right images as a pair of corresponding reference points. Besides, the efficiency of matching can be improved greatly by taking the obtained matching point as a new pair of reference points, and by updating the reference point continuously. It is proved that the proposed algorithm is valid and reliable by 3D reconstruction on two pairs of actual natural images with abundant and weak texture, respectively.展开更多
Matching features such as curve segments in stereo images play a very important role in scene recomtruction. In this paper, a stereo matching algorithm for the trajectories composed of time stamped points is proposed....Matching features such as curve segments in stereo images play a very important role in scene recomtruction. In this paper, a stereo matching algorithm for the trajectories composed of time stamped points is proposed. Based on time stamped points, planar curve match measurements are given first, such as time constraint, cross-ratio invariant constraint and eplpolar geometry constraint; then, a trajectory matching method is proposed based on epipolar geometry constraint and cross-ratio invariant constraint. In order to match the planar curve segments projected by perspective projection system, the curve start time and end time are selected first to prepare match candidates. Then, the epipolar equation is used to discard the unmatched curve segment candidates. At last, a cross ratio invariant constxaint is used to find the most matched curve segments. If their match measurement is higher than the specialized threshold, a candidate with the least cross ratio difference is then selected as the match result; otherwise, no match is found. Unlike the conventional planar curve segments matching algorithm, this paper presents a weakly calibrated binocular stereo vision system which is based on wide baseline. The stamped points are obtained by targets detecting method of flying objects from image sequences. Due to wide baseline, there must exist the projection not in epipolar monotonic order or the curve segments located in very short distance and keeping the epipolar monotonic order. By using the method mentioned above, experiments are made to match planar curve segments not only in epipolar monotonic order but also not in epipolar monotonic order. The results show that the performance of our curve matching algorithm is effective for matching the arc-like planar trajectories composed of time stamped points.展开更多
Aming at the problem of the low accuracy of low dynamic vehicle velocity under the environment of uneven distribution of light intensity,an improved adaptive Kalman filter method for the velocity error estimate by the...Aming at the problem of the low accuracy of low dynamic vehicle velocity under the environment of uneven distribution of light intensity,an improved adaptive Kalman filter method for the velocity error estimate by the fusion of optical flow tracking and scale mvaiant feature transform(SIFT)is proposed.The algorithm introduces anonlinear fuzzy membership function and the filter residual for the noise covariance matrix in the adaptive adjustment process.In the process of calculating the velocity of the vehicle,the tracking and matching of the inter-frame displacement a d the vehicle velocity calculation a e carried out by using the optical fow tracing and the SIF'T methods,respectively.Meanwhile,the velocity difference between theoutputs of thesetwo methods is used as the observation of the improved adaptive Kalman filter.Finally,the velocity calculated by the optical fow method is corrected by using the velocity error estimate of the output of the modified adaptive Kalman filter.The results of semi-physical experiments show that the maximum velocityeror of the fusion algorithm is decreased by29%than that of the optical fow method,and the computation time is reduced by80%compared with the SIFT method.展开更多
A novel method for designing chalcogenide long-period fiber grating(LPFG) sensors based on the dual-peak resonance effect of the LPFG near the phase matching turning point(PMTP) is presented. Refractive index sensing ...A novel method for designing chalcogenide long-period fiber grating(LPFG) sensors based on the dual-peak resonance effect of the LPFG near the phase matching turning point(PMTP) is presented. Refractive index sensing in a high-refractive-index chalcogenide fiber is achieved with a coated thinly clad film. The dual-peak resonant characteristics near the PMTP and the refractive index sensing properties of the LPFG are analyzed first by the phase-matching condition of the LPFG. The effects of film parameters and cladding radius on the sensitivity of refractive index sensing are further discussed. The sensor is optimized by selecting the appropriate film parameters and cladding radius. Simulation results show that the ambient refractive index sensitivity of a dual-peak coated thinly clad chalcogenide LPFG at the PMTP can be 2400 nm/RIU, which is significantly higher than that of non-optimized gratings. It has great application potential in the field of chemical sensing and biosensors.展开更多
A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low freq...A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low frequency image and several high frequency images, and the scale-invariant feature transform is employed to extract feature points from the low frequency im- age. A proximity matrix is constructed for the feature points of two related images. By singular value decomposition of the proximity matrix, a matching matrix （or matching result） reflecting the match- ing degree among feature points is obtained. Experimental results indicate that the proposed algorithm can reduce time complexity and possess a higher accuracy.展开更多
An adaptive weighted stereo matching algorithm with multilevel and bidirectional dynamic programming based on ground control points （GCPs） is presented. To decrease time complexity without losing matching precision,...An adaptive weighted stereo matching algorithm with multilevel and bidirectional dynamic programming based on ground control points （GCPs） is presented. To decrease time complexity without losing matching precision, using a multilevel search scheme, the coarse matching is processed in typical disparity space image, while the fine matching is processed in disparity-offset space image. In the upper level, GCPs are obtained by enhanced volumetric iterative algorithm enforcing the mutual constraint and the threshold constraint. Under the supervision of the highly reliable GCPs, bidirectional dynamic programming framework is employed to solve the inconsistency in the optimization path. In the lower level, to reduce running time, disparity-offset space is proposed to efficiently achieve the dense disparity image. In addition, an adaptive dual support-weight strategy is presented to aggregate matching cost, which considers photometric and geometric information. Further, post-processing algorithm can ameliorate disparity results in areas with depth discontinuities and related by occlusions using dual threshold algorithm, where missing stereo information is substituted from surrounding regions. To demonstrate the effectiveness of the algorithm, we present the two groups of experimental results for four widely used standard stereo data sets, including discussion on performance and comparison with other methods, which show that the algorithm has not only a fast speed, but also significantly improves the efficiency of holistic optimization.展开更多
Automatic Digital Orthophoto Map(DOM)generation plays an important role in many downstream works such as land use and cover detection,urban planning,and disaster assessment.Existing DOM generation methods can generate...Automatic Digital Orthophoto Map(DOM)generation plays an important role in many downstream works such as land use and cover detection,urban planning,and disaster assessment.Existing DOM generation methods can generate promising results but always need ground object filtered DEM generation before otho-rectification;this can consume much time and produce building facade contained results.To address this problem,a pixel-by-pixel digital differential rectification-based automatic DOM generation method is proposed in this paper.Firstly,3D point clouds with texture are generated by dense image matching based on an optical flow field for a stereo pair of images,respectively.Then,the grayscale of the digital differential rectification image is extracted directly from the point clouds element by element according to the nearest neighbor method for matched points.Subsequently,the elevation is repaired grid-by-grid using the multi-layer Locally Refined B-spline(LR-B)interpolation method with triangular mesh constraint for the point clouds void area,and the grayscale is obtained by the indirect scheme of digital differential rectification to generate the pixel-by-pixel digital differentially rectified image of a single image slice.Finally,a seamline network is automatically searched using a disparity map optimization algorithm,and DOM is smartly mosaicked.The qualitative and quantitative experimental results on three datasets were produced and evaluated,which confirmed the feasibility of the proposed method,and the DOM accuracy can reach 1 Ground Sample Distance(GSD)level.The comparison experiment with the state-of-the-art commercial softwares showed that the proposed method generated DOM has a better visual effect on building boundaries and roof completeness with comparable accuracy and computational efficiency.展开更多
Generating selfie images on the surface of a celestial body poses several challenges,including the position of the robotic arm,camera field of view,and limited shooting time.To address these challenges,the PCMIS(3D Po...Generating selfie images on the surface of a celestial body poses several challenges,including the position of the robotic arm,camera field of view,and limited shooting time.To address these challenges,the PCMIS(3D Point Cloud Matching Based Image Stitching)algorithm is designed,along with a corresponding shooting plan.This algorithm establishes a correspondence between depth and color information,enabling the generation of stitching views under any given view parameter.Furthermore,the algorithm is accelerated using GPU processing,resulting in a significant reduction in stitching time.The algorithm is successfully applied to generate selfie images for the Chang'e-5 mission.展开更多
基金funded by Natural Science Foundation of Jilin Province(20220101125JC)the National Natural Science Foundation of China(12273079).
文摘Lunar Laser Ranging has extremely high requirements for the pointing accuracy of the telescopes used.To improve its pointing accuracy and solve the problem of insufficiently accurate telescope pointing correction achieved by tracking stars in the all-sky region,we propose a processing scheme to select larger-sized lunar craters near the Lunar Corner Cube Retroreflector as reference features for telescope pointing bias computation.Accurately determining the position of the craters in the images is crucial for calculating the pointing bias;therefore,we propose a method for accurately calculating the crater position based on lunar surface feature matching.This method uses matched feature points obtained from image feature matching,using a deep learning method to solve the image transformation matrix.The known position of a crater in a reference image is mapped using this matrix to calculate the crater position in the target image.We validate this method using craters near the Lunar Corner Cube Retroreflectors of Apollo 15 and Luna 17 and find that the calculated position of a crater on the target image falls on the center of the crater,even for image features with large distortion near the lunar limb.The maximum image matching error is approximately 1″,and the minimum is only 0.47″,which meets the pointing requirements of Lunar Laser Ranging.This method provides a new technical means for the high-precision pointing bias calculation of the Lunar Laser Ranging system.
基金funded by the Key Laboratory of Smart Earth(No.KF2023YB01-12)the National Natural Science Foundation of China(No.42074017)+1 种基金the Key Laboratory Fund Project for Simulation of Complex Electronic Systems(614201004022210)the Chinese Academy of Sciences Youth Innovation Promotion Association(2022126)。
文摘Choosing appropriate background field data is crucial for gravity field matching navigation.Current research mainly uses gravity anomaly data or gravity gradient data as background fields.However,using gravity gradient invariants in existing research is seldom a concern.The gravity gradient tensor has three invariants,named as I_(1),I_(2)and I_(3).I_(1) is a Laplace operator outside the Earth and a Poison operator inside the Earth.The focus of this study is to discuss the performance of the other two invariants of gravity gradients in matching navigation based on the Iterative Closest Contour Point(ICCP)algorithm and compare the matching results with that of the gravity gradient Tzz.The results show that they have almost the same performance when there is no noise,and the background data noises have a large impact on the matching results.There are differences in the anti-interference ability of observation noises for the different components.Under the same random noises in the observations,I2performs a little better than the other two components in terms of position error standard deviation.According to the investigations,since attitude errors can not be avoided and influence the positioning based on Tzz,we recommend adopting invariants of gravity gradients,especially I2,for matching navigation in actual cases.
基金The National Natural Science Foundation of China(No50475041)
文摘Based on the coded and non-coded targets, the targets are extracted from the images according to their size, shape and intensity etc., and thus an improved method to identify the unique identity（D） of every coded target is put forward and the non-coded and coded targets are classified. Moreover, the gray scale centroid algorithm is applied to obtain the subpixel location of both uncoded and coded targets. The initial matching of the uncoded target correspondences between an image pair is established according to similarity and compatibility, which are based on the ID correspondences of the coded targets. The outliers in the initial matching of the uncoded target are eliminated according to three rules to finally obtain the uncoded target correspondences. Practical examples show that the algorithm is rapid, robust and is of high precision and matching ratio.
文摘Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topological Characteristics (PPTC) and Spectral Matching (SM) together to solve the afore mentioned issues. In which PPTC, a new shape descriptor, is firstly proposed. A new comparability measurement based on PPTC is defined as the matching probability. Finally, the correct matching results are achieved by the spectral matching method. The synthetic data experiments show its robustness by comparing with the other state-of-art algorithms and the real world data experiments show its effectiveness.
基金Project(61002022)supported by the National Natural Science Foundation of ChinaProject(2012M512168)supported by China Postdoctoral Science Foundation
文摘Non-rigid point matching has received more and more attention.Recently,many works have been developed to discover global relationships in the point set which is treated as an instance of a joint distribution.However,the local relationship among neighboring points is more effective under non-rigid transformations.Thus,a new algorithm taking advantage of shape context and relaxation labeling technique,called SC-RL,is proposed for non-rigid point matching.It is a strategy that joints estimation for correspondences as well as the transformation.In this work,correspondence assignment is treated as a soft-assign process in which the matching probability is updated by relaxation labeling technique with a newly defined compatibility coefficient.The compatibility coefficient is one or zero depending on whether neighboring points preserving their relative position in a local coordinate system.The comparative analysis has been performed against four state-of-the-art algorithms including SC,ICP,TPS-RPM and RPM-LNS,and the results denote that SC-RL performs better in the presence of deformations,outliers and noise.
基金Funded by the Open Researeh Fund Program of the Geomatics and Applications Laboratory,Liaoning Technical University(No.2004010).
文摘In photogrammetry and remote sensing,image matching is a basic and crucial process for automatic DEM generation.In this paper we presented a image relaxation matching method based on feature points.This method can be considered as an extention of regular grid point based matching.It avoids the shortcome of grid point based matching.For example,with this method,we can avoid low or even no texture area where errors frequently appear in cross correlaton matching.In the mean while,it makes full use of some mature techniques such as probability relaxation,image pyramid and the like which have already been successfully used in grid point matching process.Application of the technique to DEM generaton in different regions proved that it is more reasonable and reliable.
基金The National Natural Science Foundation of China under Grants(41171292,41322010)The National Basic Research Program of China(973 Program)(2012CB719904).
文摘A novel tie point matching algorithm of aerial images with the assistance of airborne LiDAR point clouds and POS data is proposed Firstly,the conjugate point searching strategy used in traditional correlation coefficient matching is improved and a fast algorithm is presented.Secondly,an automatic camera boresight misalignment calibration method based on virtual ground control points is proposed,and then the searching range of image matching is adaptively determined and applied to the image matching of the entire surveying area.Test results verified that the fast correlation coefficient matching algorithm proposed in this paper can reduce approximately 25% of the matching time without the loss of matching accuracy.The camera boresight misalignment calibration method can effectively increase the accuracy of exterior orientation elements of images calculated from POS data,and thus can significantly improve the predicted position of conjugate point for tie point matching.Our proposed image matching algorithm can achieve superior matching accuracy with multi-scale,multi-view,and cross-flight aerial images.
基金This project is supported by National Natural Science Foundation of China(No.50475176) and Municipal Natural Science Foundation of Beijing(No.KZ200511232019).
文摘A coding-based method to solve the image matching problems in stereovision measurement is presented. The solution is to add and append an identity ID to the retro-reflect point, so it can be identified efficiently under the complicated circumstances and has the characteristics of rotation, zooming, and deformation independence. Its design architecture and implementation process in details based on the theory of stereovision measurement are described. The method is effective on reducing processing data time, improving accuracy of image matching and automation of measuring system through experiments.
基金This work is supported by the Scientific Research Foundation of Bijie University.
文摘In this article, a Ky Fan matching theorem for transfer compactly open covers is established. As applications, a Fan-Browder coincidence theorem, a Ky Fan best approximation theorem and a Brouwer-Schauder-Rothe type fixed point theorem are obtained.
基金Supported by the National Natural Science Foundation of China(60905012)
文摘To improve the performance of the scale invariant feature transform （ SIFT）, a modified SIFT （M-SIFT） descriptor is proposed to realize fast and robust key-point extraction and matching. In descriptor generation, 3 rotation-invariant concentric-ring grids around the key-point location are used instead of 16 square grids used in the original SIFT. Then, 10 orientations are accumulated for each grid, which results in a 30-dimension descriptor. In descriptor matching, rough rejection mismatches is proposed based on the difference of grey information between matching points. The per- formance of the proposed method is tested for image mosaic on simulated and real-worid images. Experimental results show that the M-SIFT descriptor inherits the SIFT＇ s ability of being invariant to image scale and rotation, illumination change and affine distortion. Besides the time cost of feature extraction is reduced by 50% compared with the original SIFT. And the rough rejection mismatches can reject at least 70% of mismatches. The results also demonstrate that the performance of the pro- posed M-SIFT method is superior to other improved SIFT methods in speed and robustness.
文摘During matching on feature point, gray correlation matching technology is utilized to extract multi-peaks as a coarse matching set. A pair of given corresponding reference points within the left and right images is used to calculate gradients of reference difference between the reference points and each feature point within the multi-peaks set. The unique correspondence is determined by criterion of minimal gradients of reference difference. The obtained correspondence is taken as a new pair of reference points to update the reference points continuously until all feature points in the left (or right) image being matched with the right (or left) image. The gradients of reference difference can be calculated easily by means of pre-setting a pair of obvious feature points in the left and right images as a pair of corresponding reference points. Besides, the efficiency of matching can be improved greatly by taking the obtained matching point as a new pair of reference points, and by updating the reference point continuously. It is proved that the proposed algorithm is valid and reliable by 3D reconstruction on two pairs of actual natural images with abundant and weak texture, respectively.
基金The National Natural Science Founda-tion of China (No.60135020) and the National Defence Key Pre-research Project of China (No.413010701-3)
文摘Matching features such as curve segments in stereo images play a very important role in scene recomtruction. In this paper, a stereo matching algorithm for the trajectories composed of time stamped points is proposed. Based on time stamped points, planar curve match measurements are given first, such as time constraint, cross-ratio invariant constraint and eplpolar geometry constraint; then, a trajectory matching method is proposed based on epipolar geometry constraint and cross-ratio invariant constraint. In order to match the planar curve segments projected by perspective projection system, the curve start time and end time are selected first to prepare match candidates. Then, the epipolar equation is used to discard the unmatched curve segment candidates. At last, a cross ratio invariant constxaint is used to find the most matched curve segments. If their match measurement is higher than the specialized threshold, a candidate with the least cross ratio difference is then selected as the match result; otherwise, no match is found. Unlike the conventional planar curve segments matching algorithm, this paper presents a weakly calibrated binocular stereo vision system which is based on wide baseline. The stamped points are obtained by targets detecting method of flying objects from image sequences. Due to wide baseline, there must exist the projection not in epipolar monotonic order or the curve segments located in very short distance and keeping the epipolar monotonic order. By using the method mentioned above, experiments are made to match planar curve segments not only in epipolar monotonic order but also not in epipolar monotonic order. The results show that the performance of our curve matching algorithm is effective for matching the arc-like planar trajectories composed of time stamped points.
基金The National Natural Science Foundation of China(No.51375087,51405203)the Transformation Program of Science and Technology Achievements of Jiangsu Province(No.BA2016139)
文摘Aming at the problem of the low accuracy of low dynamic vehicle velocity under the environment of uneven distribution of light intensity,an improved adaptive Kalman filter method for the velocity error estimate by the fusion of optical flow tracking and scale mvaiant feature transform(SIFT)is proposed.The algorithm introduces anonlinear fuzzy membership function and the filter residual for the noise covariance matrix in the adaptive adjustment process.In the process of calculating the velocity of the vehicle,the tracking and matching of the inter-frame displacement a d the vehicle velocity calculation a e carried out by using the optical fow tracing and the SIF'T methods,respectively.Meanwhile,the velocity difference between theoutputs of thesetwo methods is used as the observation of the improved adaptive Kalman filter.Finally,the velocity calculated by the optical fow method is corrected by using the velocity error estimate of the output of the modified adaptive Kalman filter.The results of semi-physical experiments show that the maximum velocityeror of the fusion algorithm is decreased by29%than that of the optical fow method,and the computation time is reduced by80%compared with the SIFT method.
基金Project supported by the Natural Science Foundation of China (Grant Nos.62075107,61935006,62090064,and62090065)K.C.Wong Magna Fund in Ningbo University。
文摘A novel method for designing chalcogenide long-period fiber grating(LPFG) sensors based on the dual-peak resonance effect of the LPFG near the phase matching turning point(PMTP) is presented. Refractive index sensing in a high-refractive-index chalcogenide fiber is achieved with a coated thinly clad film. The dual-peak resonant characteristics near the PMTP and the refractive index sensing properties of the LPFG are analyzed first by the phase-matching condition of the LPFG. The effects of film parameters and cladding radius on the sensitivity of refractive index sensing are further discussed. The sensor is optimized by selecting the appropriate film parameters and cladding radius. Simulation results show that the ambient refractive index sensitivity of a dual-peak coated thinly clad chalcogenide LPFG at the PMTP can be 2400 nm/RIU, which is significantly higher than that of non-optimized gratings. It has great application potential in the field of chemical sensing and biosensors.
基金supported by the National Natural Science Foundation of China (6117212711071002)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education (20113401110006)the Innovative Research Team of 211 Project in Anhui University (KJTD007A)
文摘A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low frequency image and several high frequency images, and the scale-invariant feature transform is employed to extract feature points from the low frequency im- age. A proximity matrix is constructed for the feature points of two related images. By singular value decomposition of the proximity matrix, a matching matrix （or matching result） reflecting the match- ing degree among feature points is obtained. Experimental results indicate that the proposed algorithm can reduce time complexity and possess a higher accuracy.
基金supported by the National Natural Science Foundation of China (No.60605023,60775048)Specialized Research Fund for the Doctoral Program of Higher Education (No.20060141006)
文摘An adaptive weighted stereo matching algorithm with multilevel and bidirectional dynamic programming based on ground control points （GCPs） is presented. To decrease time complexity without losing matching precision, using a multilevel search scheme, the coarse matching is processed in typical disparity space image, while the fine matching is processed in disparity-offset space image. In the upper level, GCPs are obtained by enhanced volumetric iterative algorithm enforcing the mutual constraint and the threshold constraint. Under the supervision of the highly reliable GCPs, bidirectional dynamic programming framework is employed to solve the inconsistency in the optimization path. In the lower level, to reduce running time, disparity-offset space is proposed to efficiently achieve the dense disparity image. In addition, an adaptive dual support-weight strategy is presented to aggregate matching cost, which considers photometric and geometric information. Further, post-processing algorithm can ameliorate disparity results in areas with depth discontinuities and related by occlusions using dual threshold algorithm, where missing stereo information is substituted from surrounding regions. To demonstrate the effectiveness of the algorithm, we present the two groups of experimental results for four widely used standard stereo data sets, including discussion on performance and comparison with other methods, which show that the algorithm has not only a fast speed, but also significantly improves the efficiency of holistic optimization.
基金supported by the National Natural Science Foundation of China[Grant No.41771479]the National High-Resolution Earth Observation System(the Civil Part)[Grant No.50-H31D01-0508-13/15]the Japan Society for the Promotion of Science[Grant No.22H03573].
文摘Automatic Digital Orthophoto Map(DOM)generation plays an important role in many downstream works such as land use and cover detection,urban planning,and disaster assessment.Existing DOM generation methods can generate promising results but always need ground object filtered DEM generation before otho-rectification;this can consume much time and produce building facade contained results.To address this problem,a pixel-by-pixel digital differential rectification-based automatic DOM generation method is proposed in this paper.Firstly,3D point clouds with texture are generated by dense image matching based on an optical flow field for a stereo pair of images,respectively.Then,the grayscale of the digital differential rectification image is extracted directly from the point clouds element by element according to the nearest neighbor method for matched points.Subsequently,the elevation is repaired grid-by-grid using the multi-layer Locally Refined B-spline(LR-B)interpolation method with triangular mesh constraint for the point clouds void area,and the grayscale is obtained by the indirect scheme of digital differential rectification to generate the pixel-by-pixel digital differentially rectified image of a single image slice.Finally,a seamline network is automatically searched using a disparity map optimization algorithm,and DOM is smartly mosaicked.The qualitative and quantitative experimental results on three datasets were produced and evaluated,which confirmed the feasibility of the proposed method,and the DOM accuracy can reach 1 Ground Sample Distance(GSD)level.The comparison experiment with the state-of-the-art commercial softwares showed that the proposed method generated DOM has a better visual effect on building boundaries and roof completeness with comparable accuracy and computational efficiency.
基金supported by the Leading Goose Research and Development Program of Zhejiang Province of China under Grant No.2024C01103.
文摘Generating selfie images on the surface of a celestial body poses several challenges,including the position of the robotic arm,camera field of view,and limited shooting time.To address these challenges,the PCMIS(3D Point Cloud Matching Based Image Stitching)algorithm is designed,along with a corresponding shooting plan.This algorithm establishes a correspondence between depth and color information,enabling the generation of stitching views under any given view parameter.Furthermore,the algorithm is accelerated using GPU processing,resulting in a significant reduction in stitching time.The algorithm is successfully applied to generate selfie images for the Chang'e-5 mission.
