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Multifractal detrended fluctuation analysis parallel optimization strategy based on openMP for image processing

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成果类型:
期刊论文
作者:
Tang, Xiaoyong*;Yang, Xiaopan;Wu, Fan
通讯作者:
Tang, Xiaoyong
作者机构:
[Tang, Xiaoyong; Yang, Xiaopan] Hunan Agr Univ, Coll Informat Sci & Technol, Southern Reg Collaborat Innovat Ctr Grain & Oil C, Changsha 410128, Peoples R China.
[Wu, Fan; Tang, Xiaoyong] Hunan Univ, Sch Informat Sci & Engn, Changsha 410082, Peoples R China.
通讯机构:
[Tang, Xiaoyong] H
Hunan Agr Univ, Coll Informat Sci & Technol, Southern Reg Collaborat Innovat Ctr Grain & Oil C, Changsha 410128, Peoples R China.
Hunan Univ, Sch Informat Sci & Engn, Changsha 410082, Peoples R China.
语种:
英文
关键词:
Multifractal detrended fluctuation analysis;Hurst parameter;Parallel optimization;OpenMP
期刊:
Neural Computing and Applications
ISSN:
0941-0643
年:
2020
卷:
32
期:
10
页码:
5599-5608
机构署名:
本校为第一且通讯机构
院系归属:
信息科学技术学院
摘要:
In the past few years, multifractal detrended fluctuation analysis (MF-DFA) method has been widely applied in the field of agricultural image processing. However, the agricultural image feature MF-DFA analyses involves a great deal of iterative processes and complex matrix operations, which require massive computation and processing time. In order to reduce processing time and improve analysis efficiency, we first develop a MF-DFA program that involves image preprocessing, image segmentation, local area accumulation matrix calculation, local ar...

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