|本期目录/Table of Contents|

[1]邓雯静.基于ZigBee的无人机航拍影像快速特征匹配算法[J].电子设计工程,2019,27(22):147-151.
 DENG Wenjing.Fast feature matching algorithm for UAV aerial images based on ZigBee[J].SAMSON,2019,27(22):147-151.
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基于ZigBee的无人机航拍影像快速特征匹配算法(PDF)
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《电子设计工程》[ISSN:1674-6236/CN:61-1477/TN]

卷:
27
期数:
2019年22期
页码:
147-151
栏目:
图像分析与多媒体
出版日期:
2019-11-20

文章信息/Info

Title:
Fast feature matching algorithm for UAV aerial images based on ZigBee
文章编号:
1674-6236(2019)22-0147-05
作者:
邓雯静12
(1.重庆科技发展战略研究院有限责任公司 重庆 401123;2.《自动化与仪器仪表》编辑部 重庆 401123)
Author(s):
DENG Wen?jing
(1.Chongqing Academy of S&T for Development Co., Ltd.,Chongqing 401123,China;2. 《Automation and Instrumentation》Editorial Department,Chongqing 401123,China)
关键词:
ZigBee无人机航拍影像快速特征匹配
Keywords:
ZigBee UAV aerial image fast feature matching
分类号:
TP391
DOI:
-
文献标志码:
A
摘要:
为了提高无人机航拍影像的识别能力,需要进行特征匹配处理,提出基于ZigBee的无人机航拍影像快速特征匹配算法,采用ZigBee协议进行无人机航拍影像采集的无线传感组网设计,采集无人机航拍的图像,对图像采用局部加权融合特征分离方法进行无人机航拍影像快速特征检测,构建像素分维像模型进行无人机航拍影像快速特征匹配,使用图像的熵特征量作为特征匹配的基准分量,计算图像每个像素的局部信息熵,结合图像背景过滤机制和小目标增强方法实现对无人机航拍影像的目标细节定位和快速特征匹配。仿真结果表明,采用该方法进行无人机航拍影像快速特征匹配的自适应性较好,对图像目标的检测准确率较高。
Abstract:
In order to improve the recognition ability of UAV aerial photo image, feature matching processing is needed. A fast feature matching algorithm based on ZigBee is proposed. The wireless sensor network design of UAV aerial photo image acquisition is carried out by using ZigBee protocol. The image of UAV aerial photograph is collected, and the local weighted fusion feature separation method is used to detect the fast feature of UAV aerial photograph image, and the pixel fractal dimension image model is constructed to match the fast feature of UAV aerial photograph image. Using the entropy feature of the image as the reference component of feature matching, the local information entropy of each pixel of the image is calculated. Combined with background filtering mechanism and small target enhancement method, the target detail location and fast feature matching for UAV aerial images are realized. The simulation results show that the proposed method has good self-adaptability and high detection accuracy for UAV aerial images.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2019-05-19 稿件编号:201905087基金项目:国家重点研发计划重点专项(SQ2017YFB140322)作者简介:邓雯静(1984—),女,四川大竹人,助理工程师。研究方向:计算机信息与应用。
更新日期/Last Update: 2019-11-25