Integration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data
Integration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data
复制标题
DOI：
10.1109/tgrs.2004.843193
复制
发表时间：
2005-04
影响因子：
8.2
通讯作者：
L. Jimenez;Jorge L. Rivera-Medina;Eladio Rodriguez-Diaz;E. Arzuaga-Cruz;Mabel Ramírez-Vélez
中科院分区：
文献类型：
--
作者：
L. Jimenez;Jorge L. Rivera-Medina;Eladio Rodriguez-Diaz;E. Arzuaga-Cruz;Mabel Ramírez-Vélez
This paper presents a method of unsupervised enhancement of pixels homogeneity in a local neighborhood. This mechanism will enable an unsupervised contextual classification of multispectral data that integrates the spectral and spatial information producing results that are more meaningful to the human analyst. This unsupervised classifier is an unsupervised development of the well-known supervised extraction and classification for homogenous objects (ECHO) classifier. One of its main characteristics is that it simplifies the retrieval process of spatial structures. This development is specially relevant for the new generation of airborne and spaceborne sensors with high spatial resolution.
