A multi-index learning approach for classification of high-resolution remotely sensed images over urban areas-Reference-Cited by-同舟云学术

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A multi-index learning approach for classification of high-resolution remotely sensed images over urban areas

Published:2014-04 Issue: Volume:90 Page:36-48
ISSN:0924-2716
Container-title:ISPRS Journal of Photogrammetry and Remote Sensing
language:en
Short-container-title:ISPRS Journal of Photogrammetry and Remote Sensing

Author:

Huang Xin,Lu Qikai,Zhang Liangpei

Funder

Natural Science Foundation of China

Program for New Century Excellent Talents in University of China

Foundation for the Author of National Excellent Doctoral Dissertation of PR China (FANEDD)

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference36 articles.

1. Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses;Aguera;ISPRS J. Photogramm. Remote Sens.,2008

2. Automatic detection of residential buildings using LIDAR data and multispectral imagery;Awrangjeb;ISPRS J. Photogramm. Remote Sens.,2010

3. Object based image analysis for remote sensing;Blaschke;ISPRS J. Photogramm. Remote Sens.,2010

4. A multilevel context-based system for classification of very high spatial resolution images;Bruzzone;IEEE Trans. Geosci. Remote Sens.,2006

5. Rapid mapping of high resolution SAR scenes;Dell’Acqua;ISPRS J. Photogramm. Remote Sens.,2009

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