...
机译:新型Folded-PCA,可通过高光谱成像和SAR改进遥感中的特征提取和数据缩减
Centre for Excellence in Signal and Image Processing, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, United Kingdom;
Hyperspectral Imaging Centre, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, G1 1XW, United Kingdom;
School of Information Science and Technology, Shandong University, Jinan, China;
School of Computer Software, Tianjin University, Tianjin, China;
School of Electronic and Information Engineering, Beijing University of Aeronautics and Astronautics, China;
Centre for Excellence in Signal and Image Processing, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, United Kingdom;
School of Automation, Northwestern Polytechnical University, Xi'an, China;
Folded Principal Component Analysis (F-PCA); Feature extraction; Data reduction; Hyperspectral Imaging (HSI); Support Vector Machine (SVM); Remote sensing;
机译:使用高光谱成像进行遥感中有效的特征提取和数据缩减[应用角落]
机译:远程感测高光谱图像质量评估特征提取方法
机译:通过基于分段的折叠式PCA有效提取特征以进行高光谱图像分类
机译:遥感高光谱图像数据特征提取实验
机译:从遥感图像中基于知识的特征提取和光谱图像增强。
机译:一种从高分辨率遥感影像中提取道路信息的改进方法可增强边界信息
机译:新型折叠式PCA,可通过遥感中的高光谱成像和SAR改善特征提取和数据缩减
机译:利用LIDaR测深法对遥感海洋颜色数据解释和高光谱图像融合的查找表(LUT)方法的不断发展。