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Subpixel localization in image center is one of the key technologies of vision measurement. In order to meet the requirements of accurate calibration and measurement in multi-field, the existing sub-pixel positioning methods are complex, the positioning accuracy is greatly affected by the effect of initial edge extraction, and the positioning accuracy is low. Because remote sensing multi-view images are usually not stationary random signals, in order to better express the non-stationary characteristics of images, random analysis is combined to segment sub-pixel objects in the center of remote sensing images. The accuracy of mark positioning will affect the accuracy of the whole measurement. The control point signs with different characteristics correspond to different recognition methods, so the selection of control point marks should be based on different requirements. It is used to describe the target view from different viewpoints and use the geometric features to retrieve the model library. The matching process uses global and local, statistical and structural target recognition features hierarchically, and is divided into two steps of retrieval and exact matching. The experiment was carried out to verify the effectiveness of the method.
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篇名 Simulation of Central Subpixel Location Method in Remote Sensing Multi-View Image
来源期刊 计算机科学与技术汇刊:中英文版 学科 工学
关键词 Remote Sensing MULTI-VIEW IMAGE CENTRAL SUB-PIXEL Location
年,卷(期) 2019,(1) 所属期刊栏目
研究方向 页码范围 45-48
页数 4页 分类号 TP
字数 语种
DOI
五维指标
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研究主题发展历程
节点文献
Remote
Sensing
MULTI-VIEW
IMAGE
CENTRAL
SUB-PIXEL
Location
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
计算机科学与技术汇刊:中英文版
年刊
2327-090X
湖北省武汉市武昌区珞狮南路519号(中国
出版文献量(篇)
69
总下载数(次)
2
总被引数(次)
0
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