文件名称:Classificationofhyper_magebasedonBEMD
下载
别用迅雷、360浏览器下载。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
介绍说明－－下载内容均来自于网络，请自行研究使用
Abstract : As a powerful tool for image processing ，bi-dimensional empirical mode decomposition ( BEMD)
covers a wide range of applications． In this paper ，we explore a novel hyperspectral classification algorithm
which integrates BEMD and support vector machine ( SVM) ． By virtue of BEMD，the selected hyperspectral
bands are decomposed into several bi-dimensional intrinsic mode functions ( BIMFs) ，which reflect the essential
properties of hyperspectral image． We further make full use of SVM ，which is a supervised classification tool
widely accepted ，to classify the suitable sum of BIMFs． Experimental results indicate that though the proposed
method has no advantage in computing time ，it exhibits higher classification accuracy and stability than the clas-
sical SVM． - Abstract : As a powerful tool for image processing ，bi-dimensional empirical mode decomposition ( BEMD)
covers a wide range of applications． In this paper ，we explore a novel hyperspectral classification algorithm
which integrates BEMD and support vector machine ( SVM) ． By virtue of BEMD，the selected hyperspectral
bands are decomposed into several bi-dimensional intrinsic mode functions ( BIMFs) ，which reflect the essential
properties of hyperspectral image． We further make full use of SVM ，which is a supervised classification tool
widely accepted ，to classify the suitable sum of BIMFs． Experimental results indicate that though the proposed
method has no advantage in computing time ，it exhibits higher classification accuracy and stability than the clas-
sical SVM．
covers a wide range of applications． In this paper ，we explore a novel hyperspectral classification algorithm
which integrates BEMD and support vector machine ( SVM) ． By virtue of BEMD，the selected hyperspectral
bands are decomposed into several bi-dimensional intrinsic mode functions ( BIMFs) ，which reflect the essential
properties of hyperspectral image． We further make full use of SVM ，which is a supervised classification tool
widely accepted ，to classify the suitable sum of BIMFs． Experimental results indicate that though the proposed
method has no advantage in computing time ，it exhibits higher classification accuracy and stability than the clas-
sical SVM． - Abstract : As a powerful tool for image processing ，bi-dimensional empirical mode decomposition ( BEMD)
covers a wide range of applications． In this paper ，we explore a novel hyperspectral classification algorithm
which integrates BEMD and support vector machine ( SVM) ． By virtue of BEMD，the selected hyperspectral
bands are decomposed into several bi-dimensional intrinsic mode functions ( BIMFs) ，which reflect the essential
properties of hyperspectral image． We further make full use of SVM ，which is a supervised classification tool
widely accepted ，to classify the suitable sum of BIMFs． Experimental results indicate that though the proposed
method has no advantage in computing time ，it exhibits higher classification accuracy and stability than the clas-
sical SVM．
(系统自动生成,下载前可以参看下载内容)
下载文件列表
Classificationofhyper_magebasedonBEMD.pdf