In order to improve the autonomous navigation capability of satellite,a pulsar/CNS（celestial navigation system） integrated navigation method based on federated unscented Kalman filter（UKF） is *** celestial navigat...
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In order to improve the autonomous navigation capability of satellite,a pulsar/CNS（celestial navigation system） integrated navigation method based on federated unscented Kalman filter（UKF） is *** celestial navigation is a mature and stable navigation ***,its position determination performance is not satisfied due to the low accuracy of horizon *** pulsar navigation is a new navigation method,which can provide highly accurate range *** major drawback of single pulsar navigation is that the system is completely *** two methods are complementary to each other,the federated UKF is used here for fusing the navigation data from single pulsar navigation and *** to the traditional celestial navigation method and single pulsar navigation,the integrated navigation method can provide better navigation *** simulation results demonstrate the feasibility and effectiveness of the navigation method.
Aiming at the cu rrent structured P2P system's locality of physical location and accessing resources, in the context of P4P technology, this paper takes the Pastry algorithm as a foundation, proposes a P4P routing...
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Single nucleotide polymorphisms (SNPs) are the most common form of genetic variant in humans, which can be generally classified into disease related mutations and common ones. It has been generally accepted that SNPs ...
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Analysis on the basis of the protocol Gnutella0.6, the use P4P technologies for sensing conveniently network topology information, proposes a P4P-based Gnutella routing algorithm, in which nodes join algorithm to cons...
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Multi-spectral imaging for the analysis and preservation of ancient documents has gained high attention in recent years. While readability enhancement is based on the multi-spectral image corpus, foreground-background...
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ISBN:
(纸本)9781605587738
Multi-spectral imaging for the analysis and preservation of ancient documents has gained high attention in recent years. While readability enhancement is based on the multi-spectral image corpus, foreground-background separation still relies mainly on gray level or color images. In this paper we propose a foreground-background separation algorithm designed for multi-spectral images. The main contribution is the simultaneously utilization of spectral and spatial features. While spectral features incorporate the spectral components of the multi-spectral images, the spatial features are based on stroke properties. Higher order Markov Random Fields enables an efficient way to combine both features. To solve higher order energy functions, we introduce a new message update rule in the well known belief propagation algorithm based on a higher order potential function. Copyright 2010 ACM.
Although scene classification has been studied for decades, indoor scene recognition remains challenging due to its large view point variance and massive irregular artefacts. In fact, most existing methods for outdoor...
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An unsupervised change detection algorithm for multi-temporal satellite images based on principal component analysis (PCA) and up-down-set fuzzy Kohonen clustering network (UDSFKCN) is proposed in this paper. This met...
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An unsupervised change detection algorithm for multi-temporal satellite images based on principal component analysis (PCA) and up-down-set fuzzy Kohonen clustering network (UDSFKCN) is proposed in this paper. This method generated eigenvector corresponding to every pixel combining itself with its neighbours using principal component analysis. At the same time, the detection of the changed pixel in a region was converted into the classification between two groups, changed group and unchanged group. Since every pixel was described as one eigenvector, to obtain a changed map of the changed region at pixel level, up-down-set fuzzy Kohonen clustering network was applied to classify all the eigenvectors into changed ones and unchanged ones. Experimental results demonstrate that the proposed method has higher accuracy and stability than traditional algorithms against Gaussian and speckle noise.
This paper proposes a graph-based method for segmentation of a text image using a selected colour-channel image. The text colour information usually presents a two-polarity trend. According to the observation that the...
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The fuzzy C-means (FCM) clustering algorithm has been proven to be effective for image segmentation. However, the standard FCM algorithm is sensitive to noise and gray inhomogeneity. An improved FCM-based algorithm is...
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The fuzzy C-means (FCM) clustering algorithm has been proven to be effective for image segmentation. However, the standard FCM algorithm is sensitive to noise and gray inhomogeneity. An improved FCM-based algorithm is proposed in this paper, which firstly modeled the noise of an image as a slowly varying additive or multiplicative noise and iteratively approximate the gray inhomogeneity and noise areas by using the spatial neighborhood information. In this process, the threshold values of up and down cut-off were applied to adjust different memberships of pixel. The experimental results on the segmentation demonstrate that the algorithm performs more robust to noise than the standard FCM algorithm and MFCM algorithm.
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