[1]梁仕雄,侯北平.融合中值滤波与光流算法的云团跟踪算法[J].浙江科技学院学报,2023,(06):527-533.[doi:10.3969/j.issn.1671-8798.2023.06.008 ]
 LIANG Shixiong,HOU Beiping.Research on cloud tracking by fusion of median filtering and optical flow algorithm[J].,2023,(06):527-533.[doi:10.3969/j.issn.1671-8798.2023.06.008 ]
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融合中值滤波与光流算法的云团跟踪算法(/HTML)
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《浙江科技学院学报》[ISSN:1001-3733/CN:61-1062/R]

卷:
期数:
2023年06期
页码:
527-533
栏目:
出版日期:
2024-01-05

文章信息/Info

Title:
Research on cloud tracking by fusion of median filtering and optical flow algorithm
文章编号:
1671-8798(2023)06-0527-07
作者:
梁仕雄侯北平
(浙江科技学院 自动化与电气工程学院,杭州 310023)
Author(s):
LIANG Shixiong HOU Beiping
(School of Automation and Electrical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, Zhejiang, China)
关键词:
云团检测 图像滤波 光流算法 云团定位 目标跟踪
分类号:
TP391.41
DOI:
10.3969/j.issn.1671-8798.2023.06.008
文献标志码:
A
摘要:
【目的】针对现有的云团跟踪算法存在跟踪速率低、云团滤波边缘信息丢失、云团跟踪定位不准等问题,结合优化的中值滤波算法,提出一种融合中值滤波与光流算法的云团跟踪算法。【方法】首先对太阳的位置进行定位,采用红蓝阈值比分割图像,用优化的中值滤波算法滤除噪点后,检测云块及其质心坐标; 然后对云图序列进行光流处理,实现对云块的精确检测与实时跟踪; 最后在不同云量情况下进行云团跟踪试验,并且与传统光流算法、块匹配算法、ViBe(visual background extractor,视图背景提取)算法进行比较。【结果】本文算法在云团边缘检测和云团实时跟踪上表现优越,目标跟踪效率比其他3种算法的平均值提高了约6.32百分点。【结论】本研究结果有效解决了云团滤波导致边缘信息缺失的问题,对预测短期太阳辐照度的准确性有重要意义。

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备注/Memo

备注/Memo:
收稿日期:2022-09-23
基金项目:浙江省重点研发计划项目(2021C04030)
通信作者:侯北平(1976— ),男,山东省日照人,教授,博士,主要从事图像处理、机器视觉研究。E-mail:bphou@zust.edu.cn。
更新日期/Last Update: 2023-12-31