液晶与显示2025，Vol.40Issue(10)：1490-1508,19.DOI:10.37188/CJLCD.2025-0122
基于双因子分层约束的深度非负矩阵分解用于高光谱解混
Deep nonnegative matrix factorization with dual-factor hierarchical constraints for hyperspectral unmixing
摘要
Abstract
Hyperspectral unmixing(HU)is a key technology for addressing mixed pixels and characterizing land cover components.Although deep non-negative matrix factorization(DNMF)has shown excellent performance in HU,existing methods mostly focus on abundance modeling and neglect the multi-level feature extraction of endmembers,as well as their insufficient nonlinear representation capabilities,which limit the unmixing accuracy.To address these issues,this paper proposes a deep NMF framework for endmember hierarchical analysis,introducing inter-layer orthogonality constraints for endmember subspaces and dynamic sparse regularization for abundance refinement.Firstly,multi-level endmember decomposition is employed to enhance the nonlinear spectral feature representation.Secondly,a minimum distance guided subspace orthogonality mechanism is designed to improve the separability of endmembers,and it is coordinated with a dynamic weighted sparsity strategy to enhance the spatial consistency of abundance estimation.Finally,a two-stage hierarchical optimization algorithm is constructed,with pre-training for coarse initialization and cross-layer backpropagation for fine-tuning as the core.Experiments were conducted on two synthetic datasets and four real datasets.The results show that the SAD of the proposed method ranges from 0.004 2 to 0.078 2 and the RMSE ranges from 0.014 0 to 0.092 5 under different signal-to-noise ratios,outperforming the comparison methods by 1.42%to 5.64%and 1.87%to 6.48%respectively,verifying its accuracy and robustness.关键词
高光谱解混/深度非负矩阵分解/端元判别/正交约束/分层稀疏正则化Key words
hyperspectral unmixing/deep nonnegative matrix factorization/endmember discrimination/orthogonality constraints/hierarchical sparsity regularization分类
信息技术与安全科学引用本文复制引用
屈克文,罗小娟,保文星..基于双因子分层约束的深度非负矩阵分解用于高光谱解混[J].液晶与显示,2025,40(10):1490-1508,19.基金项目
国家自然科学基金(No.62461001) （No.62461001）
宁夏自然科学基金(No.2024AAC02035) （No.2024AAC02035）
北方民族大学研究生创新项目(No.YCX24365)Supported by National Natural Science Foundation of China(No.62461001) （No.YCX24365）
Natural Science Foundation of Ningxia(No.2024AAC02035) （No.2024AAC02035）
Innovation Project for Postgraduates of North Minzu University(No.YCX24365) （No.YCX24365）
