Research on the classification algorithm of aerial image based on the weighted mean-shift

被引：0

作者：

Guo, Qiang ^{[1
]}

Hong, Hanyu ^{[1
]}

Chen, Yichao ^{[1
]}

Zhang, Yanduo ^{[1
]}

机构：

[1] Wuhan Univ Technol, Lab Image Proc & Intelligent Control, Wuhan 430074, Peoples R China

来源：

REMOTE SENSING AND GIS DATA PROCESSING AND APPLICATIONS; AND INNOVATIVE MULTISPECTRAL TECHNOLOGY AND APPLICATIONS, PTS 1 AND 2 | 2007年 / 6790卷

关键词：

nonparametric estimate; kernel density; aerial image classification; mean shift; feature space;

D O I：

10.1117/12.751667

中图分类号：

TP7 [遥感技术];

学科分类号：

081102 ; 0816 ; 081602 ; 083002 ; 1404 ;

摘要：

The main problem of aerial image classification is how to classify with robust and high precision at present. Therefore, a new approach of the aerial image classification based on the weighted Mean Shift is proposed in this paper. The kernel density function's local maximum is found by the weighted Mean Shift filter of pixels in feature space using resamplying strategy, and the neighborhood data points are shifted to the local maximum of the region, in which the same course is implemented repeatedly to all the pixels in image. Then the classification image is got by fusing each cluster region.

引用

页数：7

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