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Robust Radiometric Normalization of the near Equatorial Satellite Images Using Feature Extraction and Remote Sensing Analysis 被引量:1
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作者 Hayder Dibs Shattri Mansor +1 位作者 Noordin Ahmad Nadhir Al-Ansari 《Engineering(科研)》 CAS 2023年第2期75-89,共15页
Relative radiometric normalization (RRN) minimizes radiometric differences among images caused by inconsistencies of acquisition conditions rather than changes in surface. Scale invariant feature transform (SIFT) has ... Relative radiometric normalization (RRN) minimizes radiometric differences among images caused by inconsistencies of acquisition conditions rather than changes in surface. Scale invariant feature transform (SIFT) has the ability to automatically extract control points (CPs) and is commonly used for remote sensing images. However, its results are mostly inaccurate and sometimes contain incorrect matching caused by generating a small number of false CP pairs. These CP pairs have high false alarm matching. This paper presents a modified method to improve the performance of SIFT CPs matching by applying sum of absolute difference (SAD) in a different manner for the new optical satellite generation called near-equatorial orbit satellite and multi-sensor images. The proposed method, which has a significantly high rate of correct matches, improves CP matching. The data in this study were obtained from the RazakSAT satellite a new near equatorial satellite system. The proposed method involves six steps: 1) data reduction, 2) applying the SIFT to automatically extract CPs, 3) refining CPs matching by using SAD algorithm with empirical threshold, and 4) calculation of true CPs intensity values over all image’ bands, 5) preforming a linear regression model between the intensity values of CPs locate in reverence and sensed image’ bands, 6) Relative radiometric normalization conducting using regression transformation functions. Different thresholds have experimentally tested and used in conducting this study (50 and 70), by followed the proposed method, and it removed the false extracted SIFT CPs to be from 775, 1125, 883, 804, 883 and 681 false pairs to 342, 424, 547, 706, 547, and 469 corrected and matched pairs, respectively. 展开更多
关键词 Relative Radiometric Normalization Scale Invariant Feature transform Automatically Extraction Control Points Sum of Absolute Difference
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An Outline of the Grand Unified Theory of Gauge Fields
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作者 Bi Qiao 《Journal of Modern Physics》 CAS 2023年第3期212-326,共25页
This paper attempts to propose a grand unified guiding principle of gauge fields from the mathematical and physical picture of fiber bundles: it is believed that our universe may have more fundamental interactions tha... This paper attempts to propose a grand unified guiding principle of gauge fields from the mathematical and physical picture of fiber bundles: it is believed that our universe may have more fundamental interactions than the four fundamental interactions, and the gauge fields of these fundamental interactions are just a unified gauge potential on the fiber bundle manifold or the components connected to the bottom manifold, that is, our universe;these components can meet the transformation of gauge potential, and even can be transformed from a fundamental interaction gauge potential to another fundamental interaction gauge potential, and can be summarized into a unified equation, namely the expression of the generalized gauge equation, corresponding to the gauge transformation invariance;so gauge transformation invariance is a necessary condition to unify field theory, but quantization of field is not a necessary condition;the four (or more) fundamental interaction fields of the universe are unified into a universal gauge field defined by the connection of the principal fiber bundle on the cosmic base manifold. 展开更多
关键词 Gauge Field Principal Fiber Bundle Gauge transformation invariance Grand Unified Theory of Physics
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Target classification using SIFT sequence scale invariants 被引量:5
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作者 Xufeng Zhu Caiwen Ma +1 位作者 Bo Liu Xiaoqian Cao 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第5期633-639,共7页
On the basis of scale invariant feature transform(SIFT) descriptors,a novel kind of local invariants based on SIFT sequence scale(SIFT-SS) is proposed and applied to target classification.First of all,the merits o... On the basis of scale invariant feature transform(SIFT) descriptors,a novel kind of local invariants based on SIFT sequence scale(SIFT-SS) is proposed and applied to target classification.First of all,the merits of using an SIFT algorithm for target classification are discussed.Secondly,the scales of SIFT descriptors are sorted by descending as SIFT-SS,which is sent to a support vector machine(SVM) with radial based function(RBF) kernel in order to train SVM classifier,which will be used for achieving target classification.Experimental results indicate that the SIFT-SS algorithm is efficient for target classification and can obtain a higher recognition rate than affine moment invariants(AMI) and multi-scale auto-convolution(MSA) in some complex situations,such as the situation with the existence of noises and occlusions.Moreover,the computational time of SIFT-SS is shorter than MSA and longer than AMI. 展开更多
关键词 target classification scale invariant feature transform descriptors sequence scale support vector machine
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Color Correction for Multi-view Video Using Energy Minimization of View Networks 被引量:4
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作者 Kenji Yamamoto Ryutaro Oi 《International Journal of Automation and computing》 EI 2008年第3期234-245,共12页
Systems using numerous cameras are emerging in many fields due to their ease of production and reduced cost, and one of the fields where they are expected to be used more actively in the near future is in image-based ... Systems using numerous cameras are emerging in many fields due to their ease of production and reduced cost, and one of the fields where they are expected to be used more actively in the near future is in image-based rendering (IBR). Color correction between views is necessary to use multi-view systems in IBR to make audiences feel comfortable when views are switched or when a free viewpoint video is displayed. Color correction usually involves two steps: the first is to adjust camera parameters such as gain, brightness, and aperture before capture, and the second is to modify captured videos through image processing. This paper deals with the latter, which does not need a color pattern board. The proposed method uses scale invariant feature transform (SIFT) to detect correspondences, treats RGB channels independently, calculates lookup tables with an energy-minimization approach, and corrects captured video with these tables. The experimental results reveal that this approach works well. 展开更多
关键词 MULTI-VIEW color correction image-based rendering (IBR) view networks (VNs) scale invariant feature transform (SIFT) energy minimization.
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Image matching algorithm based on SIFT using color and exposure information 被引量:9
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作者 Yan Zhao Yuwei Zhai +1 位作者 Eric Dubois Shigang Wang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第3期691-699,共9页
Image matching based on scale invariant feature transform(SIFT) is one of the most popular image matching algorithms, which exhibits high robustness and accuracy. Grayscale images rather than color images are genera... Image matching based on scale invariant feature transform(SIFT) is one of the most popular image matching algorithms, which exhibits high robustness and accuracy. Grayscale images rather than color images are generally used to get SIFT descriptors in order to reduce the complexity. The regions which have a similar grayscale level but different hues tend to produce wrong matching results in this case. Therefore, the loss of color information may result in decreasing of matching ratio. An image matching algorithm based on SIFT is proposed, which adds a color offset and an exposure offset when converting color images to grayscale images in order to enhance the matching ratio. Experimental results show that the proposed algorithm can effectively differentiate the regions with different colors but the similar grayscale level, and increase the matching ratio of image matching based on SIFT. Furthermore, it does not introduce much complexity than the traditional SIFT. 展开更多
关键词 scale invariant feature transform(SIFT) image matching color exposure
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Modified SIFT descriptor and key-point matching for fast and robust image mosaic 被引量:2
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作者 何玉青 王雪 +3 位作者 王思远 刘明奇 诸加丹 金伟其 《Journal of Beijing Institute of Technology》 EI CAS 2016年第4期562-570,共9页
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
关键词 modified scale invariant feature transform (SIFT) image mosaic feature extraction key-point matching
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Research on will-dimension SIFT algorithms for multi-attitude face recognition 被引量:1
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作者 SHENG Wenshun SUN Yanwen XU Liujing 《High Technology Letters》 EI CAS 2022年第3期280-287,共8页
The results of face recognition are often inaccurate due to factors such as illumination,noise intensity,and affine/projection transformation.In response to these problems,the scale invariant feature transformation(SI... The results of face recognition are often inaccurate due to factors such as illumination,noise intensity,and affine/projection transformation.In response to these problems,the scale invariant feature transformation(SIFT) is proposed,but its computational complexity and complication seriously affect the efficiency of the algorithm.In order to solve this problem,SIFT algorithm is proposed based on principal component analysis(PCA) dimensionality reduction.The algorithm first uses PCA algorithm,which has the function of screening feature points,to filter the feature points extracted in advance by the SIFT algorithm;then the high-dimensional data is projected into the low-dimensional space to remove the redundant feature points,thereby changing the way of generating feature descriptors and finally achieving the effect of dimensionality reduction.In this paper,through experiments on the public ORL face database,the dimension of SIFT is reduced to 20 dimensions,which improves the efficiency of face extraction;the comparison of several experimental results is completed and analyzed to verify the superiority of the improved algorithm. 展开更多
关键词 face recognition scale invariant feature transformation(SIFT) dimensionality reduction principal component analysis-scale invariant feature transformation(PCA-SIFT)
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An Approach to Parallelization of SIFT Algorithm on GPUs for Real-Time Applications 被引量:4
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作者 Raghu Raj Prasanna Kumar Suresh Muknahallipatna John McInroy 《Journal of Computer and Communications》 2016年第17期18-50,共33页
Scale Invariant Feature Transform (SIFT) algorithm is a widely used computer vision algorithm that detects and extracts local feature descriptors from images. SIFT is computationally intensive, making it infeasible fo... Scale Invariant Feature Transform (SIFT) algorithm is a widely used computer vision algorithm that detects and extracts local feature descriptors from images. SIFT is computationally intensive, making it infeasible for single threaded im-plementation to extract local feature descriptors for high-resolution images in real time. In this paper, an approach to parallelization of the SIFT algorithm is demonstrated using NVIDIA’s Graphics Processing Unit (GPU). The parallel-ization design for SIFT on GPUs is divided into two stages, a) Algorithm de-sign-generic design strategies which focuses on data and b) Implementation de-sign-architecture specific design strategies which focuses on optimally using GPU resources for maximum occupancy. Increasing memory latency hiding, eliminating branches and data blocking achieve a significant decrease in aver-age computational time. Furthermore, it is observed via Paraver tools that our approach to parallelization while optimizing for maximum occupancy allows GPU to execute memory bound SIFT algorithm at optimal levels. 展开更多
关键词 Scale Invariant Feature transform (SIFT) Parallel Computing GPU GPU Occupancy Portable Parallel Programming CUDA
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A Criterion for Determining the Number of Clusters 被引量:1
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作者 郝立丽 郝立柱 《Northeastern Mathematical Journal》 CSCD 2008年第6期534-544,共11页
Aiming to provide an appropriate number K of clusters, in this paper, we propose a new criterion function - H criterion function, whose three properties have also been proved. We validate the performance of the H crit... Aiming to provide an appropriate number K of clusters, in this paper, we propose a new criterion function - H criterion function, whose three properties have also been proved. We validate the performance of the H criterion function on one artificial dataset and three real-world datasets, and the results are almostly consistent with a previous method. The nonparametric criterion we proposed is intuitive, simple and the computational cost is acceptable. 展开更多
关键词 hierarchical clustering H criterion function invariance of linear transformation
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Architectural Building Detection and Tracking in Video Sequences Taken by Unmanned Aircraft System (UAS) 被引量:1
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作者 Qiang He Chee-Hung Henry Chu Aldo Camargo 《Computer Technology and Application》 2012年第9期585-593,共9页
An Unmanned Aircraft System (UAS) is an aircraft or ground station that can be either remote controlled manually or is capable of flying autonomously under the guidance of pre-programmed Global Positioning System (... An Unmanned Aircraft System (UAS) is an aircraft or ground station that can be either remote controlled manually or is capable of flying autonomously under the guidance of pre-programmed Global Positioning System (GPS) waypoint flight plans or more complex onboard intelligent systems. The UAS aircrafts have recently found extensive applications in military reconnaissance and surveillance, homeland security, precision agriculture, fire monitoring and analysis, and other different kinds of aids needed in disasters. Through surveillance videos captured by a UAS digital imaging payload over the interest areas, the corresponding UAS missions can be conducted. In this paper, the authors present an effective method to detect and extract architectural buildings under rural environment from UAS video sequences. The SIFT points are chosen as image features. The planar homography is adopted as the motion model between different image frames. The proposed algorithm is tested on real UAS video data. 展开更多
关键词 Unmanned aircraft system (UAS) object detection and tracking planar homography scale invariant feature transform(SIFT).
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Image Retrieval Based on Objects’ Spatial Orientation Relationships
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作者 CHENChuan-bo LIQi-shen GONGWen-jie 《Wuhan University Journal of Natural Sciences》 EI CAS 2005年第3期520-524,共5页
A new concept of characteristic scanning radial (CSR) is proposed for thesegmented image on the basis of two shape-specific points of its shape-objects. Subsequently, twocharacteristic attribute sequences (CAS) of rel... A new concept of characteristic scanning radial (CSR) is proposed for thesegmented image on the basis of two shape-specific points of its shape-objects. Subsequently, twocharacteristic attribute sequences (CAS) of relative distance and relative direction are derived torepresent the spatial orientation relationships among objects of the image. A novel image retrievalalgorithm is presented using these two CASs. The proposed retrieval approach not only satisfies thetransformational invariance, butalso attains the quantitative comparison of matching. Experimentsidentify the effectiveness and efficiency of the algorithm adequately. 展开更多
关键词 image retrieval spatial relationship transformation invariant shape-specific point characteristic scanning radial characteristic attribute sequence
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Approximate solutions of nonlinear PDEs by the invariant expansion
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作者 吴江龙 楼森岳 《Chinese Physics B》 SCIE EI CAS CSCD 2012年第12期31-36,共6页
It is difficult to obtain exact solutions of the nonlinear partial differential equations (PDEs) due to their complexity and nonlinearity, especially for non-integrable systems. In this paper, some reasonable approx... It is difficult to obtain exact solutions of the nonlinear partial differential equations (PDEs) due to their complexity and nonlinearity, especially for non-integrable systems. In this paper, some reasonable approximations of real physics are considered, and the invariant expansion is proposed to solve real nonlinear systems. A simple invariant expansion with quite a universal pseudopotential is used for some nonlinear PDEs such as the Korteweg-de Vries (KdV) equation with a fifth-order dispersion term, the perturbed fourth-order KdV equation, the KdV-Burgers equation, and a Boussinesq-type equation. 展开更多
关键词 approximate solution invariant expansion Mobious transformation invariance
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Wide-baseline stereo matching based on multiple views
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作者 刘亚辉 贾庆轩 +1 位作者 孙汉旭 宋荆洲 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2010年第2期225-228,共4页
To solve the problem of wide-baseline stereo image matching based on multiple cameras,the paper puts forward an image matching method of combining maximally stable extremal regions (MSER) with Scale Invariant Feature ... To solve the problem of wide-baseline stereo image matching based on multiple cameras,the paper puts forward an image matching method of combining maximally stable extremal regions (MSER) with Scale Invariant Feature Transform (SIFT) . It uses MSER to detect feature regions instead of difference of Gaussian. After fitted into elliptical regions,those regions will be normalized into unity circles and represented with SIFT descriptors. The method estimates fundamental matrix and removes outliers by auto-maximum a posteriori sample consensus after initial matching feature points. The experimental results indicate that the method is robust to viewpoint changes,can reduce computational complexity effectively and improve matching accuracy. 展开更多
关键词 image matching scale invariant feature transform maximally stable extremal region wide-baseline
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Method to generate training samples for neural network used in target recognition
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作者 何灏 罗庆生 +2 位作者 罗霄 徐如强 李钢 《Journal of Beijing Institute of Technology》 EI CAS 2012年第3期400-407,共8页
Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new meth... Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new method based on virtual model and invariant moments was proposed to generate training samples.The method was composed of the following steps:use computer and simulation software to build target object's virtual model and then simulate the environment,light condition,camera parameter,etc.;rotate the model by spin and nutation of inclination to get the image sequence by virtual camera;preprocess each image and transfer them into binary image;calculate the invariant moments for each image and get a vectors' sequence.The vectors' sequence which was proved to be complete became the training samples together with the target outputs.The simulated results showed that the proposed method could be used to recognize the real targets and improve the accuracy of target recognition effectively when the sampling interval was short enough and the circumstance simulation was close enough. 展开更多
关键词 pattern recognition training samples for neural network model emulation space coordinate transform invariant moments
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The Improved Characteristics of Bionic Gabor Representations by Combining with SIFT Key-points for Iris Recognition 被引量:6
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作者 Yuanning Liu Fei He +4 位作者 Xiaodong Zhu Zhen Liu Ying Chen Ye Han Lijiao Yu 《Journal of Bionic Engineering》 SCIE EI CSCD 2015年第3期504-517,共14页
Gabor filters are generally regarded as the most bionic filters corresponding to the visual perception of human. Their filtered coefficients thus are widely utilized to represent the texture information of irises. How... Gabor filters are generally regarded as the most bionic filters corresponding to the visual perception of human. Their filtered coefficients thus are widely utilized to represent the texture information of irises. However, these wavelet-based iris representations are inevitably being misaligned in iris matching stage. In this paper, we try to improve the characteristics of bionic Gabor representations of each iris via combining the local Gabor features and the key-point descriptors of Scale Invariant Feature Transformation (SIFT), which respectively simulate the process of visual object class recognition in frequency and spatial domains. A localized approach of Gabor features is used to avoid the blocking effect in the process of image division, meanwhile a SIFT key point selection strategy is provided to remove the noises and probable misaligned key points. For the combination of these iris features, we propose a support vector regression based fusion rule, which may fuse their matching scores to a scalar score to make classification decision. The experiments on three public and self-developed iris datasets validate the discriminative ability of our multiple bionic iris features, and also demonstrate that the fusion system outperforms some state-of-the-art methods. 展开更多
关键词 iris recognition bionic Gabor features scale invariant feature transformation support vector regression score level fusion
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Optical flow based guidance system design for semi-strapdown image homing guided missiles 被引量:5
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作者 Huang Lan Song Jianmei +1 位作者 Zhang Minqiang Cai Gaohua 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2016年第5期1345-1354,共10页
This paper focuses mainly on semi-strapdown image homing guided (SSIHG) system design based on optical flow for a six-degree-of-freedom (6-DOF) axial-symmetric skid-to-turn missile. Three optical flow algorithms s... This paper focuses mainly on semi-strapdown image homing guided (SSIHG) system design based on optical flow for a six-degree-of-freedom (6-DOF) axial-symmetric skid-to-turn missile. Three optical flow algorithms suitable for large displacements are introduced and compared. The influence of different displacements on computational accuracy of the three algorithms is analyzed statistically. The total optical flow of the SSIHG missile is obtained using the Scale Invariant Feature Transform (SIFT) algorithm, which is the best among the three for large displacements. After removing the rotational optical flow caused by rotation of the gimbal and missile body from the total optical flow, the remaining translational optical flow is smoothed via Kalman filtering. The circular navigation guidance (CNG) law with impact angle constraint is then obtained utilizing the smoothed translational optical flow and position of the target image. Simulations are carried out under both disturbed and undisturbed conditions, and results indicate the proposed guidance strategy for SSIHG missiles can result in a precise target hit with a desired impact angle without the need for the time-to-go parameter. 展开更多
关键词 Guidance strategy Impact angle Optical flow Scale Invariant Feature transform (SIFT) Semi-strapdown image homing guided (SSIHG) missile
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Image Forgery Detection Using Segmentation and Swarm Intelligent Algorithm 被引量:2
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作者 ZHAO Fei SHI Wenchang +1 位作者 QIN Bo LIANG Bin 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2017年第2期141-148,共8页
Small or smooth cloned regions are difficult to be detected in image copy-move forgery (CMF) detection. Aiming at this problem, an effective method based on image segmentation and swarm intelligent (SI) algorithm ... Small or smooth cloned regions are difficult to be detected in image copy-move forgery (CMF) detection. Aiming at this problem, an effective method based on image segmentation and swarm intelligent (SI) algorithm is proposed. This method segments image into small nonoverlapping blocks. A calculation of smooth degree is given for each block. Test image is segmented into independent layers according to the smooth degree. SI algorithm is applied in finding the optimal detection parameters for each layer. These parameters are used to detect each layer by scale invariant features transform (SIFT)-based scheme, which can locate a mass of keypoints. The experimental results prove the good performance of the proposed method, which is effective to identify the CMF image with small or smooth cloned region. 展开更多
关键词 copy-move forgery detection scale invariant features transform (SIFT) swarm intelligent algorithm particle swarm optimization
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Super-resolution enhancement of UAV images based on fractional calculus and POCS 被引量:2
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作者 Junfeng Lei Shangyue Zhang +2 位作者 Li Luo Jinsheng Xiao He Wang 《Geo-Spatial Information Science》 SCIE CSCD 2018年第1期56-66,共11页
A super-resolution enhancement algorithm was proposed based on the combination of fractional calculus and Projection onto Convex Sets(POCS)for unmanned aerial vehicles(UAVs)images.The representative problems of UAV im... A super-resolution enhancement algorithm was proposed based on the combination of fractional calculus and Projection onto Convex Sets(POCS)for unmanned aerial vehicles(UAVs)images.The representative problems of UAV images including motion blur,fisheye effect distortion,overexposed,and so on can be improved by the proposed algorithm.The fractional calculus operator is used to enhance the high-resolution and low-resolution reference frames for POCS.The affine transformation parameters between low-resolution images and reference frame are calculated by Scale Invariant Feature Transform(SIFT)for matching.The point spread function of POCS is simulated by a fractional integral filter instead of Gaussian filter for more clarity of texture and detail.The objective indices and subjective effect are compared between the proposed and other methods.The experimental results indicate that the proposed method outperforms other algorithms in most cases,especially in the structure and detail clarity of the reconstructed images. 展开更多
关键词 Unmanned aerial vehicle(UAV)image SUPERRESOLUTION fractional calculus Projection onto Convex Sets(POCS) Scale Invariant Feature transform(SIFT)
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SWF-SIFT Approach for Infrared Face Recognition 被引量:1
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作者 谭春林 汪洪桥 裴得利 《Tsinghua Science and Technology》 SCIE EI CAS 2010年第3期357-362,共6页
The scale invariant feature transform (SIFT) feature descriptor is invariant to image scale and location, and is robust to affine transformations and changes in illumination, so it is a powerful descriptor used in m... The scale invariant feature transform (SIFT) feature descriptor is invariant to image scale and location, and is robust to affine transformations and changes in illumination, so it is a powerful descriptor used in many applications, such as object recognition, video tracking, and gesture recognition. However, in noisy and non-rigid object recognition applications, especially for infrared human face recognition, SIFT-based algorithms may mismatch many feature points. This paper presents a star-styled window filter-SIFT (SWF-SIFT) scheme to improve the infrared human face recognition performance by filtering out incorrect matches. Performance comparisons between the SIFT and SWF-SIFT algorithms show the advantages of the SWF-SIFT algorithm through tests using a typical infrared human face database. 展开更多
关键词 infrared image human face recognition scale invariant feature transform (SIFT) star-styled window filter (SWF)
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Detecting Designated Building Areas From Remote Sensing Images Using Hierarchical Structural Constraints
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作者 Fukun BI Mingyang LEI +2 位作者 Zhihua YANG Jinyuan HOU Yanyan QIN 《Photonic Sensors》 SCIE EI CSCD 2020年第1期45-56,共12页
Automatic detection of a designated building area(DBA)is a research hotspot in the field of target detection using remote sensing images.Target detection is urgently needed for tasks such as illegal building monitorin... Automatic detection of a designated building area(DBA)is a research hotspot in the field of target detection using remote sensing images.Target detection is urgently needed for tasks such as illegal building monitoring,dynamic land use monitoring,antiterrorism efforts,and military reconnaissance.The existing detection methods generally have low efficiency and poor detection accuracy due to the large size and complexity of remote sensing scenes.To address the problems of the current detection methods,this paper presents a DBA detection method that uses hierarchical structural constraints in remote sensing images.Our method was conducted in two main stages.(1)During keypoint generation,we proposed a screening method based on structural pattern descriptors.The local pattern feature of the initial keypoints was described by a multilevel local pattern histogram(MLPH)feature;then,we used one-class support vector machine(OC-SVM)merely to screen those building attribute keypoints.(2)To match the screened keypoints,we proposed a reliable DBA detection method based on matching the local structural similarities of the screened keypoints.We achieved precise keypoint matching by calculating the similarities of the local skeletal structures in the neighboring areas around the roughly matched keypoints to achieve DBA detection.We tested the proposed method on building area sets of different types and at different time phases.The experimental results show that the proposed method is both highly accurate and computationally efficient. 展开更多
关键词 DBA detection local structural constraint multilevel local pattern histogram(MLPH) similarity of the local structure scale invariant feature transform(SIFT)
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