基于结构稀疏模型的高光谱影像亚像元级分类和超分辨率制图技术研究

项目名称： 基于结构稀疏模型的高光谱影像亚像元级分类和超分辨率制图技术研究

项目编号： No.61271022

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 无线电电子学、电信技术

项目作者： 贾森

作者单位： 深圳大学

项目金额： 80万元

中文摘要： 申请人主持的青年科学基金项目(编号：60902070)通过基于概率模型的非负矩阵分解、基于图模型的仿射传播聚类、Gabor小波变换、Memetic混合搜索等方法对高光谱影像的去噪、特征提取/选择、解混、分类等关键问题进行了比较深入的研究，在国际权威期刊和会议上发表论文多篇(SCI收录6篇，EI收录15篇)。 本项目重点研究基于结构稀疏模型的高光谱影像亚像元级分类和超分辨率制图技术。在探讨结构稀疏的模型构建及优化算法基础上，研究高光谱影像的结构稀疏表达机理，设计基于结构稀疏模型的稀疏变换/分解、结构特征选择/提取、结构稀疏分类方法，建立像元分类与光谱解混之间的联合表达和分析机制，实现联合结构稀疏的亚像元级分类；进一步融入光谱间的互补信息、空间的相关信息和先验知识，实现多模态结构稀疏的超分辨率制图。形成比较系统的结构稀疏理论和方法，为高光谱影像的亚像元级分类和超分辨率制图提供新的理论和工具。

中文关键词： 高光谱影像；模式分类；稀疏表达；；

英文摘要： The young scientist fund of NSFC (Grant No. 60902070) chaired by the applicant has intensively studied the key problems of hyperspectral imagery, including denoising, feature extraction/selection, unmixing and classification, through probabilistic model-based nonnegative matrix factorization, graphical model-based affinity propagation clustering, Gabor wavelet transform, Memetic hybrid search, etc. Several papers have been published on international top journals and conferences, among which, six are indexed by SCI and fifteen indexed by EI. The project mainly focuses on structured sparse model-based hyperspectral imagery sub-pixel classification and super-resolution mapping techniques. Based on the investigation of model construction and optimization algorithms of structured sparsity, the structured sparse expression mechanism of hyperspectral imagery is examined. The structured sparse model-based sparse transformation/decomposition, structural feature selection/extraction, structure sparse classification approaches are developed. The co-expression and analysis mechanism between pixel classification and spectral unmixing are established, implementing joint structured sparse sub-pixel classification. Further, multi-modal structured sparse super-resolution mapping is accomplished by integrating the complementary i

英文关键词： hyperspectral imagery；pattern classification；sparse representation；；