This paper aims at providing multi-source remote sensing images registered in geometric space for image fusion.Focusing on the characteristics and differences of multi-source remote sensing images,a feature-based regi...This paper aims at providing multi-source remote sensing images registered in geometric space for image fusion.Focusing on the characteristics and differences of multi-source remote sensing images,a feature-based registration algorithm is implemented.The key technologies include image scale-space for implementing multi-scale properties,Harris corner detection for keypoints extraction,and partial intensity invariant feature descriptor(PIIFD)for keypoints description.Eventually,a multi-scale Harris-PIIFD image registration algorithm framework is proposed.The experimental results of fifteen sets of representative real data show that the algorithm has excellent,stable performance in multi-source remote sensing image registration,and can achieve accurate spatial alignment,which has strong practical application value and certain generalization ability.展开更多
To develop a quick, accurate and antinoise automated image registration technique for infrared images, the wavelet analysis technique was used to extract the feature points in two images followed by the compensation f...To develop a quick, accurate and antinoise automated image registration technique for infrared images, the wavelet analysis technique was used to extract the feature points in two images followed by the compensation for input image with angle difference between them. A hi erarchical feature matching algorithm was adopted to get the final transform parameters between the two images. The simulation results for two infrared images show that the method can effectively, quickly and accurately register images and be antinoise to some extent.展开更多
Technique s for constructing full view panoramic mosaics from sequences of images are pres ented. The goal of this work is to remove too many limitations for pure panning motion. The best reference block is important...Technique s for constructing full view panoramic mosaics from sequences of images are pres ented. The goal of this work is to remove too many limitations for pure panning motion. The best reference block is important for the block-matching method for improving the robustness and performance. It is automatically selected in the h igh-frequency image, which always contains the plenty visible features. In orde r to reduce accumulated registration errors, the global registration using the p hase-correlation matching method with rotation adjustment is applied to the who le sequence of images, which results in an optimal image mosaic with resolving t ranslational or rotational motion. The local registration using the Levenberg-M arquardt iterative non-linear minimization algorithm is applied to compensating for small amounts of motion parallax introduced by translations of the camera a nd other unmodeled distortions, then minimizing the discrepancy after applying t he global registration. The accumulated misregistration errors may cause a visib le gap between the two images. A smoothing filter is introduced for removing the visible artifact.展开更多
In order to improve the registration accuracy of brain magnetic resonance images(MRI),some deep learning registration methods use segmentation images for training model.How-ever,the segmentation values are constant fo...In order to improve the registration accuracy of brain magnetic resonance images(MRI),some deep learning registration methods use segmentation images for training model.How-ever,the segmentation values are constant for each label,which leads to the gradient variation con-centrating on the boundary.Thus,the dense deformation field(DDF)is gathered on the boundary and there even appears folding phenomenon.In order to fully leverage the label information,the morphological opening and closing information maps are introduced to enlarge the non-zero gradi-ent regions and improve the accuracy of DDF estimation.The opening information maps supervise the registration model to focus on smaller,narrow brain regions.The closing information maps supervise the registration model to pay more attention to the complex boundary region.Then,opening and closing morphology networks(OC_Net)are designed to automatically generate open-ing and closing information maps to realize the end-to-end training process.Finally,a new registra-tion architecture,VM_(seg+oc),is proposed by combining OC_Net and VoxelMorph.Experimental results show that the registration accuracy of VM_(seg+oc) is significantly improved on LPBA40 and OASIS1 datasets.Especially,VM_(seg+oc) can well improve registration accuracy in smaller brain regions and narrow regions.展开更多
An automatic image registration approach based on wavelet transform is proposed. This proposed method utilizes multiscale wavelet transform to extract feature points. A coarse-to-fine feature matching method is utiliz...An automatic image registration approach based on wavelet transform is proposed. This proposed method utilizes multiscale wavelet transform to extract feature points. A coarse-to-fine feature matching method is utilized in the feature matching phase. A two-way matching method based on cross-correlation to get candidate point pairs and a fine matching based on support strength combine to form the matching algorithm. At last, based on an affine transformation model, the parameters are iteratively refined by using the leastsquares estimation approach. Experimental results have verified that the proposed algorithm can realize automatic registration of various kinds of images rapidly and effectively.展开更多
Combined with the printing application,an image registration method based on the multi-resolution morphology contour detection was proposed.First,a direction based multi-resolution gray morphology in the scheme was pr...Combined with the printing application,an image registration method based on the multi-resolution morphology contour detection was proposed.First,a direction based multi-resolution gray morphology in the scheme was proposed to realize the contour extraction.Then,based on the contour features,the subspace image registration was proposed to deal with issues of the computing complexity appeared in the traditional image registration methods.The proposed image registration was efficiently applied in the defect inspection of printing images.展开更多
For the purpose of identifying the stern of the SWATH （Small Waterplane Area Twin Hull） availably and perfecting the detection technique of the SWATH ship＇s performance, this paper presents a novel bidirectional im...For the purpose of identifying the stern of the SWATH （Small Waterplane Area Twin Hull） availably and perfecting the detection technique of the SWATH ship＇s performance, this paper presents a novel bidirectional image registration strategy and mosaicing technique based on the scale invariant feature transform （SIFT） algorithm. The proposed method can help us observe the stern with a great visual angle for analyzing the performance of the control fins of the SWATH. SIFT is one of the most effective local features of the scale, rotation and illumination invariant. However, there are a few false match rates in this algorithm. In terms of underwater machine vision, only by acquiring an accurate match rate can we find an underwater robot rapidly and identify the location of the object. Therefore, firstly, the selection of the match ratio principle is put forward in this paper; secondly, some advantages of the bidirectional registration algorithm are concluded by analyzing the characteristics of the unidirectional matching method. Finally, an automatic underwater image splicing method is proposed on the basis of fixed dimension, and then the edge of the image＇s overlapping section is merged by the principal components analysis algorithm. The experimental results achieve a better registration and smooth mosaicing effect, demonstrating that the proposed method is effective.展开更多
In this paper, a facial feature extracting method is proposed to transform three-dimension （3D） head images of infants with deformational plagiocephaly for assessment of asymmetry. The features of 3D point clouds of...In this paper, a facial feature extracting method is proposed to transform three-dimension （3D） head images of infants with deformational plagiocephaly for assessment of asymmetry. The features of 3D point clouds of an infant＇s cranium can be identified by local feature analysis and a two-phase k-means classification algorithm. The 3D images of infants with asymmetric cranium can then be aligned to the same pose. The mirrored head model obtained from the symmetry plane is compared with the original model for the measurement of asymmetry. Numerical data of the cranial volume can be reviewed by a pediatrician to adjust the treatment plan. The system can also be used to demonstrate the treatment progress.展开更多
文摘This paper aims at providing multi-source remote sensing images registered in geometric space for image fusion.Focusing on the characteristics and differences of multi-source remote sensing images,a feature-based registration algorithm is implemented.The key technologies include image scale-space for implementing multi-scale properties,Harris corner detection for keypoints extraction,and partial intensity invariant feature descriptor(PIIFD)for keypoints description.Eventually,a multi-scale Harris-PIIFD image registration algorithm framework is proposed.The experimental results of fifteen sets of representative real data show that the algorithm has excellent,stable performance in multi-source remote sensing image registration,and can achieve accurate spatial alignment,which has strong practical application value and certain generalization ability.
文摘To develop a quick, accurate and antinoise automated image registration technique for infrared images, the wavelet analysis technique was used to extract the feature points in two images followed by the compensation for input image with angle difference between them. A hi erarchical feature matching algorithm was adopted to get the final transform parameters between the two images. The simulation results for two infrared images show that the method can effectively, quickly and accurately register images and be antinoise to some extent.
文摘Technique s for constructing full view panoramic mosaics from sequences of images are pres ented. The goal of this work is to remove too many limitations for pure panning motion. The best reference block is important for the block-matching method for improving the robustness and performance. It is automatically selected in the h igh-frequency image, which always contains the plenty visible features. In orde r to reduce accumulated registration errors, the global registration using the p hase-correlation matching method with rotation adjustment is applied to the who le sequence of images, which results in an optimal image mosaic with resolving t ranslational or rotational motion. The local registration using the Levenberg-M arquardt iterative non-linear minimization algorithm is applied to compensating for small amounts of motion parallax introduced by translations of the camera a nd other unmodeled distortions, then minimizing the discrepancy after applying t he global registration. The accumulated misregistration errors may cause a visib le gap between the two images. A smoothing filter is introduced for removing the visible artifact.
基金supported by Shandong Provincial Natural Science Foundation(No.ZR2023MF062)the National Natural Science Foundation of China(No.61771230).
文摘In order to improve the registration accuracy of brain magnetic resonance images(MRI),some deep learning registration methods use segmentation images for training model.How-ever,the segmentation values are constant for each label,which leads to the gradient variation con-centrating on the boundary.Thus,the dense deformation field(DDF)is gathered on the boundary and there even appears folding phenomenon.In order to fully leverage the label information,the morphological opening and closing information maps are introduced to enlarge the non-zero gradi-ent regions and improve the accuracy of DDF estimation.The opening information maps supervise the registration model to focus on smaller,narrow brain regions.The closing information maps supervise the registration model to pay more attention to the complex boundary region.Then,opening and closing morphology networks(OC_Net)are designed to automatically generate open-ing and closing information maps to realize the end-to-end training process.Finally,a new registra-tion architecture,VM_(seg+oc),is proposed by combining OC_Net and VoxelMorph.Experimental results show that the registration accuracy of VM_(seg+oc) is significantly improved on LPBA40 and OASIS1 datasets.Especially,VM_(seg+oc) can well improve registration accuracy in smaller brain regions and narrow regions.
文摘An automatic image registration approach based on wavelet transform is proposed. This proposed method utilizes multiscale wavelet transform to extract feature points. A coarse-to-fine feature matching method is utilized in the feature matching phase. A two-way matching method based on cross-correlation to get candidate point pairs and a fine matching based on support strength combine to form the matching algorithm. At last, based on an affine transformation model, the parameters are iteratively refined by using the leastsquares estimation approach. Experimental results have verified that the proposed algorithm can realize automatic registration of various kinds of images rapidly and effectively.
基金Funded by the National Natural Science Foundation of China(General Program,Key Program,Major Research Plan) (Grant No.60474021)China Postdoctoral Science Foundation (Grant No.20100471180)the Freedom Explore Program of Central South University (Grant No. 2012QNZT017)
文摘Combined with the printing application,an image registration method based on the multi-resolution morphology contour detection was proposed.First,a direction based multi-resolution gray morphology in the scheme was proposed to realize the contour extraction.Then,based on the contour features,the subspace image registration was proposed to deal with issues of the computing complexity appeared in the traditional image registration methods.The proposed image registration was efficiently applied in the defect inspection of printing images.
基金Supported by the "Liaoning Baiqianwan" Talents Program(No.200718625)the Program of Scientific Research Project of Liao Ning Province Education Commission(No.LS2010046)the National Commonweal Industry Scientific Research Project(No.201003024)
文摘For the purpose of identifying the stern of the SWATH （Small Waterplane Area Twin Hull） availably and perfecting the detection technique of the SWATH ship＇s performance, this paper presents a novel bidirectional image registration strategy and mosaicing technique based on the scale invariant feature transform （SIFT） algorithm. The proposed method can help us observe the stern with a great visual angle for analyzing the performance of the control fins of the SWATH. SIFT is one of the most effective local features of the scale, rotation and illumination invariant. However, there are a few false match rates in this algorithm. In terms of underwater machine vision, only by acquiring an accurate match rate can we find an underwater robot rapidly and identify the location of the object. Therefore, firstly, the selection of the match ratio principle is put forward in this paper; secondly, some advantages of the bidirectional registration algorithm are concluded by analyzing the characteristics of the unidirectional matching method. Finally, an automatic underwater image splicing method is proposed on the basis of fixed dimension, and then the edge of the image＇s overlapping section is merged by the principal components analysis algorithm. The experimental results achieve a better registration and smooth mosaicing effect, demonstrating that the proposed method is effective.
文摘In this paper, a facial feature extracting method is proposed to transform three-dimension （3D） head images of infants with deformational plagiocephaly for assessment of asymmetry. The features of 3D point clouds of an infant＇s cranium can be identified by local feature analysis and a two-phase k-means classification algorithm. The 3D images of infants with asymmetric cranium can then be aligned to the same pose. The mirrored head model obtained from the symmetry plane is compared with the original model for the measurement of asymmetry. Numerical data of the cranial volume can be reviewed by a pediatrician to adjust the treatment plan. The system can also be used to demonstrate the treatment progress.
