Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm

doi:10.1371/journal.pone.0177666

	Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm
	Wang, Xingmei 1; Liu, Shu 2; Liu, Zhipeng 3
	2017-05-18
发表期刊	PLOS ONE
ISSN	1932-6203
卷号	12 期号:5 页码:30
摘要	This paper proposes a combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm to detect underwater objects in sonar images. Specifically, for the first time, the problem of inappropriate filtering degree parameter which commonly occurs in non-local spatial information and seriously affects the denoising performance in sonar images, was solved with the method utilizing a novel filtering degree parameter. Then, a quantum-inspired shuffled frog leaping algorithm based on new search mechanism (QSFLA-NSM) is proposed to precisely and quickly detect sonar images. Each frog individual is directly encoded by real numbers, which can greatly simplify the evolution process of the quantum-inspired shuffled frog leaping algorithm (QSFLA). Meanwhile, a fitness function combining intra-class difference with inter-class difference is adopted to evaluate frog positions more accurately. On this basis, recurring to an analysis of the quantum-behaved particle swarm optimization (QPSO) and the shuffled frog leaping algorithm (SFLA), a new search mechanism is developed to improve the searching ability and detection accuracy. At the same time, the time complexity is further reduced. Finally, the results of comparative experiments using the original sonar images, the UCI data sets and the benchmark functions demonstrate the effectiveness and adaptability of the proposed method.
DOI	10.1371/journal.pone.0177666
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[41306086] ; technology innovation talent special foundation of Harbin[2014RFQXJ105] ; Fundamental Research Funds for the Central Universities[HEUCF100606] ; China Scholarship Council (CSC)[201506685079]
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:000401672400065
出版者	PUBLIC LIBRARY SCIENCE
引用统计	被引频次：18[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/7229
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Wang, Xingmei
作者单位	1.Harbin Engn Univ, Coll Comp Sci & Technol, Harbin, Heilongjiang, Peoples R China 2.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc CAS, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Wang, Xingmei,Liu, Shu,Liu, Zhipeng. Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm[J]. PLOS ONE,2017,12(5):30.
APA	Wang, Xingmei,Liu, Shu,&Liu, Zhipeng.(2017).Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm.PLOS ONE,12(5),30.
MLA	Wang, Xingmei,et al."Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm".PLOS ONE 12.5(2017):30.