Nonnegative Multiresolution Representation-Based Texture Image Classification

doi:10.1145/2738050

OPT OpenIR > 光谱成像技术研究室

	Nonnegative Multiresolution Representation-Based Texture Image Classification
	Dong, Yongsheng 1,2; Tao, Dacheng1 ; Li, Xuelong1
	2015-10-01
发表期刊	ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY
卷号	7 期号:1
摘要	Effective representation of image texture is important for an image-classification task. Statistical modelling in wavelet domains has been widely used to image texture representation. However, due to the intraclass complexity and interclass diversity of textures, it is hard to use a predefined probability distribution function to fit adaptively all wavelet subband coefficients of different textures. In this article, we propose a novel modelling approach, Heterogeneous and Incrementally Generated Histogram (HIGH), to indirectly model the wavelet coefficients by use of four local features in wavelet subbands. By concatenating all the HIGHs in all wavelet subbands of a texture, we can construct a nonnegative multiresolution vector (NMV) to represent a texture image. Considering the NMV's high dimensionality and nonnegativity, we further propose a Hessian regularized discriminative nonnegative matrix factorization to compute a low-dimensional basis of the linear subspace of NMVs. Finally, we present a texture classification approach by projecting NMVs on the low-dimensional basis. Experimental results show that our proposed texture classification method outperforms seven representative approaches.
文章类型	Article
关键词	Theory Experimentation Nonnegative Matrix Factorization Texture Classification Histogram Manifold Regularization Hessian Regularization
WOS标题词	Science & Technology ; Technology
DOI	10.1145/2738050
收录类别	SCI ; EI
关键词[WOS]	GENERALIZED GAUSSIAN DENSITY ; LOCAL BINARY PATTERNS ; MATRIX FACTORIZATION ; FEATURE-EXTRACTION ; MODEL ; RECOGNITION ; RETRIEVAL ; FEATURES ; TRANSFORM ; SUBSPACE
语种	英语
WOS研究方向	Computer Science
项目资助者	National Natural Science Foundation of China(61125106 ; China Post-Doctoral Science Foundation(2014M550517 ; Key Research Program of the Chinese Academy of Sciences(KGZD-EW-T03) ; Program for Innovative Research Team (in Science and Technology) in University of Henan Province(14IRTSTHN021) ; Key Science and Technology Research Project of Henan Provinces Education Department of China(13B520992) ; 61301230) ; 2015T81063)
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Information Systems
WOS记录号	WOS:000363900100004
引用统计	被引频次：14[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.opt.ac.cn/handle/181661/25540
专题	光谱成像技术研究室
作者单位	1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China 2.Henan Univ Sci & Technol, Informat Engn Coll, Luoyang 471023, Henan, Peoples R China
推荐引用方式 GB/T 7714	Dong, Yongsheng,Tao, Dacheng,Li, Xuelong. Nonnegative Multiresolution Representation-Based Texture Image Classification[J]. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,2015,7(1).
APA	Dong, Yongsheng,Tao, Dacheng,&Li, Xuelong.(2015).Nonnegative Multiresolution Representation-Based Texture Image Classification.ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,7(1).
MLA	Dong, Yongsheng,et al."Nonnegative Multiresolution Representation-Based Texture Image Classification".ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 7.1(2015).

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