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Artikel ; Online: Dual-Graph Global and Local Concept Factorization for Data Clustering.

Li, Ning / Leng, Chengcai / Cheng, Irene / Basu, Anup / Jiao, Licheng

IEEE transactions on neural networks and learning systems

2022 Band PP

Abstract: Considering a wide range of applications of nonnegative matrix factorization (NMF), many NMF and their variants have been developed. Since previous NMF methods cannot fully describe complex inner global and local manifold structures of the data space and ...

Abstract	Considering a wide range of applications of nonnegative matrix factorization (NMF), many NMF and their variants have been developed. Since previous NMF methods cannot fully describe complex inner global and local manifold structures of the data space and extract complex structural information, we propose a novel NMF method called dual-graph global and local concept factorization (DGLCF). To properly describe the inner manifold structure, DGLCF introduces the global and local structures of the data manifold and the geometric structure of the feature manifold into CF. The global manifold structure makes the model more discriminative, while the two local regularization terms simultaneously preserve the inherent geometry of data and features. Finally, we analyze convergence and the iterative update rules of DGLCF. We illustrate clustering performance by comparing it with latest algorithms on four real-world datasets.
Sprache	Englisch
Erscheinungsdatum	2022-06-02
Erscheinungsland	United States
Dokumenttyp	Journal Article
ISSN	2162-2388
ISSN (online)	2162-2388
DOI	10.1109/TNNLS.2022.3177433
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Multimodal Remote Sensing Image Registration Methods and Advancements: A Survey

Zhang, Xinyue / Leng, Chengcai / Hong, Yameng / Pei, Zhao / Cheng, Irene / Basu, Anup

Remote Sensing. 2021 Dec. 17, v. 13, no. 24

2021

Abstract: With rapid advancements in remote sensing image registration algorithms, comprehensive imaging applications are no longer limited to single-modal remote sensing images. Instead, multi-modal remote sensing (MMRS) image registration has become a research ... ...

Abstract	With rapid advancements in remote sensing image registration algorithms, comprehensive imaging applications are no longer limited to single-modal remote sensing images. Instead, multi-modal remote sensing (MMRS) image registration has become a research focus in recent years. However, considering multi-source, multi-temporal, and multi-spectrum input introduces significant nonlinear radiation differences in MMRS images for which researchers need to develop novel solutions. At present, comprehensive reviews and analyses of MMRS image registration methods are inadequate in related fields. Thus, this paper introduces three theoretical frameworks: namely, area-based, feature-based and deep learning-based methods. We present a brief review of traditional methods and focus on more advanced methods for MMRS image registration proposed in recent years. Our review or comprehensive analysis is intended to provide researchers in related fields with advanced understanding to achieve further breakthroughs and innovations.
Schlagwörter	algorithms ; image analysis ; remote sensing ; researchers ; surveys
Sprache	Englisch
Erscheinungsverlauf	2021-1217
Erscheinungsort	Multidisciplinary Digital Publishing Institute
Dokumenttyp	Artikel
ZDB-ID	2513863-7
ISSN	2072-4292
ISSN	2072-4292
DOI	10.3390/rs13245128
Datenquelle	NAL Katalog (AGRICOLA)

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Artikel: HOLBP: Remote Sensing Image Registration Based on Histogram of Oriented Local Binary Pattern Descriptor

Hong, Yameng / Leng, Chengcai / Zhang, Xinyue / Pei, Zhao / Cheng, Irene / Basu, Anup

Remote Sensing. 2021 June 14, v. 13, no. 12

2021

Abstract: Image registration has always been an important research topic. This paper proposes a novel method of constructing descriptors called the histogram of oriented local binary pattern descriptor (HOLBP) for fast and robust matching. There are three new ... ...

Abstract	Image registration has always been an important research topic. This paper proposes a novel method of constructing descriptors called the histogram of oriented local binary pattern descriptor (HOLBP) for fast and robust matching. There are three new components in our algorithm. First, we redefined the gradient and angle calculation template to make it more sensitive to edge information. Second, we proposed a new construction method of the HOLBP descriptor and improved the traditional local binary pattern (LBP) computation template. Third, the principle of uniform rotation-invariant LBP was applied to add 10-dimensional gradient direction information to form a 138-dimension HOLBP descriptor vector. The experimental results showed that our method is very stable in terms of accuracy and computational time for different test images.
Schlagwörter	algorithms ; clothing ; image analysis ; remote sensing ; testing
Sprache	Englisch
Erscheinungsverlauf	2021-0614
Erscheinungsort	Multidisciplinary Digital Publishing Institute
Dokumenttyp	Artikel
ZDB-ID	2513863-7
ISSN	2072-4292
ISSN	2072-4292
DOI	10.3390/rs13122328
Datenquelle	NAL Katalog (AGRICOLA)

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Artikel ; Online: Occluded-Object 3D Reconstruction Using Camera Array Synthetic Aperture Imaging.

Pei, Zhao / Li, Yawen / Ma, Miao / Li, Jun / Leng, Chengcai / Zhang, Xiaoqiang / Zhang, Yanning

Sensors (Basel, Switzerland)

2019 Band 19, Heft 3

Abstract: With the three-dimensional (3D) coordinates of objects captured by a sequence of images taken in different views, object reconstruction is a technique which aims to recover the shape and appearance information of objects. Although great progress in ... ...

Abstract	With the three-dimensional (3D) coordinates of objects captured by a sequence of images taken in different views, object reconstruction is a technique which aims to recover the shape and appearance information of objects. Although great progress in object reconstruction has been made over the past few years, object reconstruction in occlusion situations remains a challenging problem. In this paper, we propose a novel method to reconstruct occluded objects based on synthetic aperture imaging. Unlike most existing methods, which either assume that there is no occlusion in the scene or remove the occlusion from the reconstructed result, our method uses the characteristics of synthetic aperture imaging that can effectively reduce the influence of occlusion to reconstruct the scene with occlusion. The proposed method labels occlusion pixels according to variance and reconstructs the 3D point cloud based on synthetic aperture imaging. Accuracies of the point cloud are tested by calculating the spatial difference between occlusion and non-occlusion conditions. The experiment results show that the proposed method can handle the occluded situation well and demonstrates a promising performance.
Sprache	Englisch
Erscheinungsdatum	2019-01-31
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s19030607
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Graph Matching Based on Stochastic Perturbation.

Leng, Chengcai / Xu, Wei / Cheng, Irene / Basu, Anup

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

2015 Band 24, Heft 12, Seite(n) 4862–4875

Abstract: This paper presents a novel perspective on characterizing the spectral correspondence between the nodes of weighted graphs for image matching applications. The algorithm is based on the principal feature components obtained by stochastic perturbation of ... ...

Abstract	This paper presents a novel perspective on characterizing the spectral correspondence between the nodes of weighted graphs for image matching applications. The algorithm is based on the principal feature components obtained by stochastic perturbation of a graph. There are three areas of contributions in this paper. First, a stochastic normalized Laplacian matrix of a weighted graph is obtained by perturbing the matrix of a sensed graph model. Second, we obtain the eigenvectors based on an eigen-decomposition approach, where representative elements of each row of this matrix can be considered to be the feature components of a feature point. Third, correct correspondences are determined in a low-dimensional principal feature component space between the graphs. In order to further enhance image matching, we also exploit the random sample consensus algorithm, as a post-processing step, to eliminate mismatches in feature correspondences. The experiments on synthetic and real-world images demonstrate the effectiveness and accuracy of the proposed method.
Sprache	Englisch
Erscheinungsdatum	2015-12
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1941-0042
ISSN (online)	1941-0042
DOI	10.1109/TIP.2015.2469153
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Robust adaptive principal component analysis based on intergraph matrix for medical image registration.

Leng, Chengcai / Xiao, Jinjun / Li, Min / Zhang, Haipeng

Computational intelligence and neuroscience

2015 Band 2015, Seite(n) 829528

Abstract: This paper proposes a novel robust adaptive principal component analysis (RAPCA) method based on intergraph matrix for image registration in order to improve robustness and real-time performance. The contributions can be divided into three parts. Firstly, ...

Abstract	This paper proposes a novel robust adaptive principal component analysis (RAPCA) method based on intergraph matrix for image registration in order to improve robustness and real-time performance. The contributions can be divided into three parts. Firstly, a novel RAPCA method is developed to capture the common structure patterns based on intergraph matrix of the objects. Secondly, the robust similarity measure is proposed based on adaptive principal component. Finally, the robust registration algorithm is derived based on the RAPCA. The experimental results show that the proposed method is very effective in capturing the common structure patterns for image registration on real-world images.
Mesh-Begriff(e)	Brain/anatomy & histology ; Diagnostic Imaging/methods ; Humans ; Image Interpretation, Computer-Assisted/methods ; Principal Component Analysis
Sprache	Englisch
Erscheinungsdatum	2015
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2388208-6
ISSN	1687-5273 ; 1687-5265
ISSN (online)	1687-5273
ISSN	1687-5265
DOI	10.1155/2015/829528
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Reconstruction Method for Optical Tomography Based on the Linearized Bregman Iteration with Sparse Regularization.

Leng, Chengcai / Yu, Dongdong / Zhang, Shuang / An, Yu / Hu, Yifang

Computational and mathematical methods in medicine

2015 Band 2015, Seite(n) 304191

Abstract: Optical molecular imaging is a promising technique and has been widely used in physiology, and pathology at cellular and molecular levels, which includes different modalities such as bioluminescence tomography, fluorescence molecular tomography and ... ...

Abstract	Optical molecular imaging is a promising technique and has been widely used in physiology, and pathology at cellular and molecular levels, which includes different modalities such as bioluminescence tomography, fluorescence molecular tomography and Cerenkov luminescence tomography. The inverse problem is ill-posed for the above modalities, which cause a nonunique solution. In this paper, we propose an effective reconstruction method based on the linearized Bregman iterative algorithm with sparse regularization (LBSR) for reconstruction. Considering the sparsity characteristics of the reconstructed sources, the sparsity can be regarded as a kind of a priori information and sparse regularization is incorporated, which can accurately locate the position of the source. The linearized Bregman iteration method is exploited to minimize the sparse regularization problem so as to further achieve fast and accurate reconstruction results. Experimental results in a numerical simulation and in vivo mouse demonstrate the effectiveness and potential of the proposed method.
Mesh-Begriff(e)	Algorithms ; Animals ; Computer Simulation ; Humans ; Image Processing, Computer-Assisted/methods ; Image Processing, Computer-Assisted/statistics & numerical data ; Linear Models ; Mice ; Mice, Nude ; Models, Statistical ; Tomography, Optical/statistics & numerical data ; X-Ray Microtomography/statistics & numerical data
Sprache	Englisch
Erscheinungsdatum	2015
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2252430-7
ISSN	1748-6718 ; 1748-670X ; 1027-3662
ISSN (online)	1748-6718
ISSN	1748-670X ; 1027-3662
DOI	10.1155/2015/304191
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Fast Rotation-Free Feature-Based Image Registration Using Improved N-SIFT and GMM-Based Parallel Optimization.

Yu, Dongdong / Yang, Feng / Yang, Caiyun / Leng, Chengcai / Cao, Jian / Wang, Yining / Tian, Jie

IEEE transactions on bio-medical engineering

2016 Band 63, Heft 8, Seite(n) 1653–1664

Abstract: Image registration is a key problem in a variety of applications, such as computer vision, medical image processing, pattern recognition, etc., while the application of registration is limited by time consumption and the accuracy in the case of large ... ...

Abstract	Image registration is a key problem in a variety of applications, such as computer vision, medical image processing, pattern recognition, etc., while the application of registration is limited by time consumption and the accuracy in the case of large pose differences. Aimed at these two kinds of problems, we propose a fast rotation-free feature-based rigid registration method based on our proposed accelerated-NSIFT and GMM registration-based parallel optimization (PO-GMMREG). Our method is accelerated by using the GPU/CUDA programming and preserving only the location information without constructing the descriptor of each interest point, while its robustness to missing correspondences and outliers is improved by converting the interest point matching to Gaussian mixture model alignment. The accuracy in the case of large pose differences is settled by our proposed PO-GMMREG algorithm by constructing a set of initial transformations. Experimental results demonstrate that our proposed algorithm can fast rigidly register 3-D medical images and is reliable for aligning 3-D scans even when they exhibit a poor initialization.
Mesh-Begriff(e)	Algorithms ; Brain/diagnostic imaging ; Heart/diagnostic imaging ; Humans ; Image Processing, Computer-Assisted/methods ; Imaging, Three-Dimensional ; Magnetic Resonance Imaging ; Normal Distribution
Sprache	Englisch
Erscheinungsdatum	2016-08
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	160429-6
ISSN	1558-2531 ; 0018-9294
ISSN (online)	1558-2531
ISSN	0018-9294
DOI	10.1109/TBME.2015.2465855
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: L

Hu, Yifang / Liu, Jie / Leng, Chengcai / An, Yu / Zhang, Shuang / Wang, Kun

Molecular imaging and biology

2016 Band 18, Heft 6, Seite(n) 830–837

Abstract: Purpose: Bioluminescence tomography (BLT) is a promising in vivo optical imaging technique in preclinical research at cellular and molecular levels. The problem of BLT reconstruction is quite ill-posed and ill-conditioned. In order to achieve high ... ...

Abstract	Purpose: Bioluminescence tomography (BLT) is a promising in vivo optical imaging technique in preclinical research at cellular and molecular levels. The problem of BLT reconstruction is quite ill-posed and ill-conditioned. In order to achieve high accuracy and efficiency for its inverse reconstruction, we proposed a novel approach based on L Procedures: The diffusion equation was used as the forward model. Then, we defined the objective function of L Results: The results of the simulations indicated that compared with the conjugate gradient and iterative shrinkage methods, the proposed method is more accurate and faster for multisource reconstructions. Furthermore, in vivo imaging suggested that it could clearly distinguish the viable and apoptotic tumor regions. Conclusions: The Split Bregman iteration method is able to minimize the L
Mesh-Begriff(e)	Algorithms ; Animals ; Computer Simulation ; Image Processing, Computer-Assisted ; Luminescent Measurements/methods ; Mice, Inbred BALB C ; Mice, Nude ; Phantoms, Imaging ; Tomography, Optical/methods ; Tomography, X-Ray Computed
Sprache	Englisch
Erscheinungsdatum	2016-06-08
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2079160-4
ISSN	1860-2002 ; 1536-1632
ISSN (online)	1860-2002
ISSN	1536-1632
DOI	10.1007/s11307-016-0970-9
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Reconstruction Method for In Vivo Bioluminescence Tomography Based on the Split Bregman Iterative and Surrogate Functions.

Zhang, Shuang / Wang, Kun / Liu, Hongbo / Leng, Chengcai / Gao, Yuan / Tian, Jie

Molecular imaging and biology

2016 Band 19, Heft 2, Seite(n) 245–255

Abstract: Purpose: Bioluminescence tomography (BLT) can provide in vivo three-dimensional (3D) images for quantitative analysis of biological processes in preclinical small animal studies, which is superior than the conventional planar bioluminescence imaging. ... ...

Abstract	Purpose: Bioluminescence tomography (BLT) can provide in vivo three-dimensional (3D) images for quantitative analysis of biological processes in preclinical small animal studies, which is superior than the conventional planar bioluminescence imaging. However, to reconstruct light sources under the skin in 3D with desirable accuracy and efficiency, BLT has to face the ill-posed and ill-conditioned inverse problem. In this paper, we developed a new method for BLT reconstruction, which utilized the mathematical strategies of the split Bregman iterative and surrogate functions (SBISF) method. Procedures: The proposed method considered the sparsity characteristic of the reconstructed sources. Thus, the sparsity itself was regarded as a kind of a priori information, and the sparse regularization is incorporated, which can accurately locate the position of the sources. Numerical simulation experiments of multisource cases with comparative analyses were performed to evaluate the performance of the proposed method. Then, a bead-implanted mouse and a breast cancer xenograft mouse model were employed to validate the feasibility of this method in in vivo experiments. Results: The results of both simulation and in vivo experiments indicated that comparing with the L1-norm iteration shrinkage method and non-monotone spectral projected gradient pursuit method, the proposed SBISF method provided the smallest position error with the least amount of time consumption. Conclusions: The SBISF method is able to achieve high accuracy and high efficiency in BLT reconstruction and hold great potential for making BLT more practical in small animal studies.
Mesh-Begriff(e)	Algorithms ; Animals ; Imaging, Three-Dimensional ; Luminescent Measurements/methods ; Mice, Inbred BALB C ; Mice, Nude ; Numerical Analysis, Computer-Assisted ; Tomography, Optical/methods ; Xenograft Model Antitumor Assays
Sprache	Englisch
Erscheinungsdatum	2016-08-26
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2079160-4
ISSN	1860-2002 ; 1536-1632
ISSN (online)	1860-2002
ISSN	1536-1632
DOI	10.1007/s11307-016-1002-5
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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