Optimizing multiscale segmentation with local spectral heterogeneity measure for high resolution remote sensing images-Reference-Cited by-同舟云学术

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Optimizing multiscale segmentation with local spectral heterogeneity measure for high resolution remote sensing images

Published:2019-11 Issue: Volume:157 Page:13-25
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:

Shen Yu,Chen Jianyu,Xiao Liang,Pan Delu

Funder

NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization

National Key Research and Development Program of China

National Natural Science Foundation of China

Jiangsu Provincial Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

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

Reference49 articles.

1. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information;Benz;ISPRS J. Photogramm. Remote Sens.,2004

2. Geographic object-based image analysis - towards a new paradigm;Blaschke;ISPRS J. Photogramm. Remote Sens.,2014

3. On the objectivity of the objective function problems with unsupervised segmentation evaluation based on global score and a possible remedy;Böck;Remote Sens.,2017

4. Toward a generic evaluation of image segmentation;Cardoso;IEEE Trans. Image Process.,2005

5. Geographic object-based image analysis (GEOBIA): Emerging trends and future opportunities;Chen;GIScience Remote Sens.,2018

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