Remote sensing image registration has been a very important research topic, especially the registration of heterologous images. In the research of the past few years, numerous registration algorithms for heterogenic i...
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Remote sensing image registration has been a very important research topic, especially the registration of heterologous images. In the research of the past few years, numerous registration algorithms for heterogenic images have been developed, especially feature-based matching algorithms, such as point feature-based or line feature-based matching methods. However, there are few matching algorithms that combine line and point features. Therefore, this study proposes a matching algorithm that combines line features and point features while achieving good rotation invariance. It comprises LSD detection of line features, keypoint extraction, and HOG-like feature descriptor construction. The matching performance is compared with state-of-the-art matching algorithms on three heterogeneous image datasets (optical-SAR dataset, optical-infrared dataset, and optical-optical dataset), verifying our method's rotational invariance by rotating images in each dataset. Finally, the experimental results show that our algorithm outperforms the state-of-the-art algorithms in terms of matching performance while possessing very good rotation invariance.
Image registration is an important step in remote sensing image preprocessing. The accuracy, efficiency, and automatic degree of image registration will directly affect the results of subsequent image processing and a...
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Image registration is an important step in remote sensing image preprocessing. The accuracy, efficiency, and automatic degree of image registration will directly affect the results of subsequent image processing and analysis. Due to the slow registration speed and low registration accuracy of SIFT algorithm for GF-2 panchromatic and multispectral remote sensing images, SIFT algorithm is improved in this article to improve the efficiency of image registration algorithm. In this article, the strategy of information entropy meshes is introduced, and feature extraction is carried out only for the regions with large information entropy, so that the running time of feature extraction can be reduced. By introducing Canny operator to eliminate the unstable edge response points, the number of feature points can be further reduced, thus the computation amount of the algorithm can be also reduced. Due to the poor registration effect of SIFT algorithm for remote sensing images, a new gradient calculation method and feature description method are used in this article to enhance the robustness of feature descriptors. In the feature matching stage, this article proposes a two-layer matching strategy, which uses mutual Euclidean distance for initial matching, then uses fsc algorithm for fine matching, and finally realizes the registration of GF-2 panchromatic and multispectral remote sensing images. Experimental results show that the proposed algorithm can obtain more correct matching point pairs when the number of extracted feature points is small. Moreover, the registration accuracy and speed are both higher than the comparison algorithm. This article uses the remote sensing images of urban scenes dominated by plains and mountainous scenes with small terrain fluctuation respectively for experiments. The algorithm in this article can achieve registration accuracy better than 0.5 pixels, and in terms of time consumption, it is only about 70% of SIFT algorithm, and the computational
Aim at the problem that the most of algorithm for community discovery assume that community don't overlap with each other,the paper combined with spectrum graph theory and fuzzy sets theory to analyze the communit...
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ISBN:
(纸本)9781467349994
Aim at the problem that the most of algorithm for community discovery assume that community don't overlap with each other,the paper combined with spectrum graph theory and fuzzy sets theory to analyze the community structures in complex networks,the paper proposes a fuzzy spectral clustering algorithmfsc for discovery overlapping *** basic idea of fsc is to describe communities membership of network nodes with membership degree function,the community of each node belong to the community by the *** two different types of real network simulation,the results demonstrate the feasibility and effectiveness of the approach.
The proposed liquid-crystal and backlight (LC/BL) algorithm presents the dynamic field-sequential-color (D-fsc) algorithm to reduce the color-breakup (CBU) effect without greatly increasing the subframe rate. The D-FS...
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The proposed liquid-crystal and backlight (LC/BL) algorithm presents the dynamic field-sequential-color (D-fsc) algorithm to reduce the color-breakup (CBU) effect without greatly increasing the subframe rate. The D-fsc algorithm can intelligently select one adequate color sequence from multiple color sequences according to the image data. In other words, the scope of CBU suppression of the proposed LC/BL algorithm is more extensive than other conventional fscs. Simulation results show that the CBU suppression can be improved substantially by the proposed evaluation equation.
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