叶沅鑫, 单杰, 熊金鑫, 董来根. 一种结合SIFT和边缘信息的多源遥感影像匹配方法[J]. 武汉大学学报 ( 信息科学版), 2013, 38(10): 1148-1151.
引用本文: 叶沅鑫, 单杰, 熊金鑫, 董来根. 一种结合SIFT和边缘信息的多源遥感影像匹配方法[J]. 武汉大学学报 ( 信息科学版), 2013, 38(10): 1148-1151.
YE Yuanxin, SHAN Jie, XIONG Jinxin, DONG Laigen. A Node Localization Method in Wireless Sensor Network Based on K-means Cluster[J]. Geomatics and Information Science of Wuhan University, 2013, 38(10): 1148-1151.
Citation: YE Yuanxin, SHAN Jie, XIONG Jinxin, DONG Laigen. A Node Localization Method in Wireless Sensor Network Based on K-means Cluster[J]. Geomatics and Information Science of Wuhan University, 2013, 38(10): 1148-1151.

一种结合SIFT和边缘信息的多源遥感影像匹配方法

A Node Localization Method in Wireless Sensor Network Based on K-means Cluster

  • 摘要: 针对多源遥感影像间几何变形和灰度差异造成的匹配困难问题,提出一种结合SIFT和边缘信息的影像匹配方法。首先在高斯差分尺度空间进行特征点检测,并采用相位一致性提取可靠的边缘信息;然后结合改进的SIFT和形状上下文对特征点进行描述;最后将欧氏距离和χ2统计作为相似性测度获取同名点。相比于SIFT算法,本文方法可有效地提高匹配正确率,并获得更多的同名点。

     

    Abstract: Considering the influence of the environmental difference in the same localization circumstance, we proposes a node localization algorithm based on clustering in this paper. This algorithm can realize nodes clustering by using the RSSI-similarity degree in space environment, and succeed in localization estimation with different model parameters. Experimental results show that the proposed algorithm has a better localization accuracy than some RSSI algorithm.

     

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