eprintid: 2097
rev_number: 11
eprint_status: archive
userid: 297
dir: disk0/00/00/20/97
datestamp: 2016-12-06 05:11:13
lastmod: 2016-12-06 05:11:13
status_changed: 2016-12-06 05:11:13
type: article
metadata_visibility: show
creators_name: Luu, Viet Hung
creators_name: Pham, Van Manh
creators_name: Man, Duc Chuc
creators_name: Bui, Quang Hung
creators_name: Nguyen, Thi Nhat Thanh
creators_id: hungbq@vnu.edu.vn
creators_id: thanhntn@vnu.edu.vn
title: Comparison of Various Image Fusion Methods for Impervious Surface Classification from VNREDSat-1
ispublished: pub
subjects: IT
divisions: FIMO
divisions: fac_fit
abstract: Impervious surfaces are important indicators for urban development  monitoring. Accurate mapping of urban impervious surfaces with observational satellites, such as VNREDSat-1,  remains challenging due to the spectral diversity not captured by an individual PAN image. In this article, five  multi-resolution image fusion techniques were compared for the task of classifting urban impervious  surfaces. The result shows that for VNREDSat-1 dataset, UNB and Wavelet tranformation methods are the best  techniques in reserving spatial and spectral information of original MS image, respectively. However, the UNB  technique gives the best results when it comes to impervious surface classification, especially in the  case of shadow areas included in non-impervious surface group.
date: 2016-06
date_type: published
publisher: The International Promotion Agency of Culture Technology
official_url: http://www.earticle.net/article.aspx?sn=278787
id_number: 10.17703/IJACT.2016.4.2.1
full_text_status: public
publication: International Journal of Advanced Culture Technology (IJACT)
volume: 4
number: 2
pagerange: 1-6
refereed: TRUE
citation:   Luu, Viet Hung and Pham, Van Manh and Man, Duc Chuc and Bui, Quang Hung and Nguyen, Thi Nhat Thanh  (2016) Comparison of Various Image Fusion Methods for Impervious Surface Classification from VNREDSat-1.  International Journal of Advanced Culture Technology (IJACT), 4  (2).   pp. 1-6.      
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2097/1/article.aspx_sn%3D278787