- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Remote Sensing Image Registration based on Phase Congruency Feature Detection and Spatial Constraint Matching
摘要： In this paper, a novel remote sensing image registration method based on phase congruency (PC) and spatial constraint is proposed. PC can provide intrinsic and meaningful image features, even when there are complex intensity changes or noise. Image features will be well detected from the corresponding PC images by the SAR-SIFT operator. It means that the feature detection methods in the frequency domain (PC) and the spatial domain (SAR-SIFT operator) are combined. To further improve the result of registration, spatial constraints, including point and line constraint, are established by utilizing the position and orientation information. Then, one to more matches can be removed and the influence of adjacent point can be greatly eliminated. The experimental results demonstrate that our method can obtain a better registration performance with higher accuracy and more correct correspondences than the state-of-the-art methods, such as SIFT, SAR-SIFT, SURF, PSO-SIFT, RIFT, and GLPM.
关键词： remote sensing,spatial constraint,SAR-SIFT operator,image registration,Phase congruency
更新于2025-09-23 15:23:52
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[IEEE 2018 6th International Conference on Multimedia Computing and Systems (ICMCS) - Rabat (2018.5.10-2018.5.12)] 2018 6th International Conference on Multimedia Computing and Systems (ICMCS) - Image Mosaicing Review: application on solar plant frames
摘要： The creation of mosaic image from a collection of video frames has been an attractive research area because of its wide range of applications in recent years. So as definition; mosaicing is a process of stitching of multiple images to generate a single, large and wide view image. In this paper we present a survey on image mosaicing; area of use by presenting some related works used this technique in various fields, then techniques and algorithms, we provide the application of this techniques on solar plant frames, also we discuss advantages and disadvantages of all mosaicing methods.
关键词： stitching,image mosaicing,RANSAC,blending,SIFT
更新于2025-09-23 15:22:29
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[IEEE 2018 26th European Signal Processing Conference (EUSIPCO) - Rome (2018.9.3-2018.9.7)] 2018 26th European Signal Processing Conference (EUSIPCO) - Unsupervised calibration of RGB-NIR capture pairs utilizing dense multimodal image correspondences
摘要： In this paper, we propose an unsupervised calibration framework aimed at calibrating RGB plus Near-InfraRed (NIR) capture setups. We favour dense feature matching for the case of multimodal data and utilize the Scale-Invariant Feature Transform (SIFT) flow, previously developed for matching same-category image objects. We develop an optimization procedure that minimizes the global disparity field between the two multimodal images in order to adapt SIFT flow for our calibration needs. The proposed optimization substantially increases the number of inliers and yields more robust and unambiguous calibration results.
关键词： multimodal stereo,calibration,SIFT flow,NIR,features matching
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Bag-of-Visual Words and Error-Correcting Output Codes for Multilabel Classification of Remote Sensing Images
摘要： This paper presents a novel framework for multilabel classification of remote sensing images using Error-Correcting Output Codes (ECOC). Starting with a set of primary class labels, the proposed framework consists in transforming the multiclass problem into binary learning subproblems. The distributed output representations of these binary learners are then transformed into primary class labels. In order to obtain robustness with respect to scale, rotation and image content, a Bag-of-Visual Words (BOVW) model based on Scale Invariant Feature Transform (SIFT) descriptors is used for feature extraction. BOVW assumes an a-priori unsupervised learning of a dictionary of visual words over the training set. Experiments are performed on GeoEye-1 images and the results show the effectiveness of the proposed approach towards multilabel classification, if compared to other methods.
关键词： Multilabel classification,SIFT,BOVW,ECOC
更新于2025-09-23 15:21:21
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[IEEE 2019 18th International Conference on Optical Communications and Networks (ICOCN) - Huangshan, China (2019.8.5-2019.8.8)] 2019 18th International Conference on Optical Communications and Networks (ICOCN) - Image Registration SIFT Algorithm Based on Adaptive Adjustment of Grayscale Weight
摘要： In view of the low color contrast of the foreground in the image of aero-engine blades, this paper optimizes the SIFT algorithm which was commonly used in image registration. The SSIM index and FSIM index in the image similarity evaluation standard are added to calculate. Using the ESFS index as the judgment standard for analysing the similarity between the color image and the corresponding grayscale image. To calculate a weight ratio which is better than the traditional algorithm. Experiments show that the proposed algorithm outperforms traditional algorithm in saving the blade images’ information, and can acquire more feature point pairs in the subsequent SIFT registration process.
关键词： Edge Structure and Feature Similarity (ESFS),Scale-invariant Feature Transform(SIFT),Feature Similarity(FSIM),Structural Similarity(SSIM)
更新于2025-09-23 15:21:01
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Building Extraction from High-Resolution Remotely Sensed Imagery Based on Multi-subgraph Matching
摘要： Building extraction is still a dif?cult issue in the ?eld of remote sensing. In order to extract the buildings with similar structures ef?ciently, an algorithm based on multi-subgraph matching is proposed using only the panchromatic high-resolution remotely sensed imagery (RSI). Firstly, scale-invariant feature transform feature is detected within both RSI and building template, and the corresponding graphs are constructed. Then, binary matching rules are de?ned to reconstruct the graphs to reduce the complexity. At last, according to the homogeneity of the building top, disconnected subgraphs are isolated from the reconstructed graphs. To improve the algorithm accuracy, the matched subgraphs are optimized on the basis of the differences in the structure and size. For verifying the validity of the proposed method, nine representatives are chosen from GF-2 images covering Guangzhou, China. Experimental results show that the precision and recall of the proposed method are 97.73% and 87.16%, respectively, and its overall performance F1 is higher than the three other similar methods.
关键词： Building extraction,Remotely sensed imagery,Multi-subgraph matching,Graph segmentation,SIFT
更新于2025-09-23 15:21:01
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Research on velocity measurement of hypersonic turbulent boundary layer based on nano-tracer-based planar laser scattering technique
摘要： With the flight speed of the aircraft increasing, hypersonic aerodynamics has become one of the hot spots in the field of aerodynamics. As one of the most typical flow structures in hypersonic flow, the hypersonic turbulent boundary layer (TBL) is of great significance to optimize the aerodynamic configuration design of a hypersonic vehicle. At the same time, flow information measurement of hypersonic TBLs will not only help us understand the mechanism of hypersonic TBL, but also provide sufficient calibration datum for numerical simulation.
关键词： SIFT (scale invariant feature transformation),NPLS technique,Velocity measurement,Hypersonic turbulent boundary layer
更新于2025-09-23 15:19:57
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Research and application of key technologies for medical image intelligence knowledge discovery and data processing
摘要： The hospital has accumulated a large amount of medical image data which needs to be analyzed and integrated so as to be able to find the needed medical image in time, which is the basis of key technologies such as intelligent diagnosis of diseases. Meanwhile, through the analysis and integrated processing of medical image, the potential value of existing medical image data can be fully explored. In this paper, the key technologies in the intelligent image knowledge discovery system and the characteristics of medical image data are studied and improved. In this paper, the characteristics of knowledge discovery and medical image data are comprehensively considered, and RDM texture features are selected as the feature representation of medical images. An improved RDM operator is proposed and proved by experimental results. Experimental results show that the improved RDM coding method can improve the stability of medical image data expression.
关键词： Improved RDM Operator,SIFT characteristics,Medical image intelligence knowledge discovery
更新于2025-09-16 10:30:52
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Photovoltaic defect classification through thermal infrared imaging using a machine learning approach
摘要： This study examines a deep learning and feature-based approach for the purpose of detecting and classifying defective photovoltaic modules using thermal infrared images in a South African setting. The VGG-16 and MobileNet models are shown to provide good performance for the classification of defects. The scale invariant feature transform (SIFT) descriptor, combined with a random forest classifier, is used to identify defective photovoltaic modules. The implementation of this approach has potential for cost reduction in defect classification over current methods.
关键词： photovoltaic,SIFT,machine learning,defect classification,random forest,deep learning,support vector machine,defect detection,infrared thermography
更新于2025-09-12 10:27:22
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Masked SIFT with Align-Based Refinement for Contactless Palmprint Recognition
摘要： Contactless palmprint is considered more user convenient than other biometrics due to its acquisition simplicity and less-private nature. Many challenges arise which affect the performance of common contact-based methods when applied to contactless environment. For example, pose and illumination variations affect the layout and visibility of palm lines. This paper proposes a SIFT-based method with three main modifications from the traditional SIFT. First, the palm regions with no significant lines/wrinkles are masked out to reduce the false features. A region with multi lines are then described by multi descriptors rather than a single one. Second, instead of comparing all query keypoints with all target ones, only those with small rotation difference are matched together. This speed-up the comparison process and enhance the accuracy, compared with SIFT, by reducing the wrong matches. Third, an align-based refinement is applied to filter out the incorrect matches. The method is tested on three contactless hand databases; IITD, GPDS and Sfax-Miracl. It achieves a verification equal error rate of 0.72%, 0.84% and 1.14% and a correct identification rate of 98.9%, 99% and 98.9% on each database, respectively. These results are significantly better than the state-of-art methods on same databases by 1.9% for verification and 3.2% for identification.
关键词： SIFT,Contactless palmprint,Biometrics,MaskedSIFT,Align-Based Refinement,Selective Matching
更新于2025-09-10 09:29:36