Comparison of segmentation techniques remotely sensed images for land cover features

This study presents the comparison of edge and region-based segmentation approaches in segmenting linear and polygonal land cover features respectively in optical, single polarization SAR, and multi-polarization SAR images which covered the area of Asajaya, Sarawak and Kuala Nerus, Terengganu. To se...

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Main Author:	Lee, Ken Yoong
Format:	Thesis
Language:	English
Published:	2003
Subjects:	G Geography Anthropology Recreation
Online Access:	http://eprints.utm.my/id/eprint/42622/1/LeeCheeHongMFKKKSA2004.pdf
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id	my-utm-ep.42622
record_format	uketd_dc
spelling	my-utm-ep.426222017-10-19T11:01:13Z Comparison of segmentation techniques remotely sensed images for land cover features 2003 Lee, Ken Yoong G Geography. Anthropology. Recreation This study presents the comparison of edge and region-based segmentation approaches in segmenting linear and polygonal land cover features respectively in optical, single polarization SAR, and multi-polarization SAR images which covered the area of Asajaya, Sarawak and Kuala Nerus, Terengganu. To segment the linear features, the procedures included: edge detection, edge map transformation, edge thinning, and edge linking. From the results obtained, the kernel-based first derivative (i.e. Frei-Chen, Kirsch, Prewitt, and Sobel) gave the better outcomes based on the identification accuracy computed. The segmentation was, however, bounded by two factors: (l) the sensitivity of edge detectors to image texture and (2) the characteristics of input data. For polygonal features, three different region-based segmentors, namely centroid linkage region grower, split-and-merge, and morphological watershed transform, were applied to the following inputs: (1) spectral (or SAR backscattering) data alone, (2) texture data alone, and (3) combined spectral (or SAR backscattering) and textural data. In this study, it was found that the centroid linkage region growing was superior to the split-and-merge and watershed transform. The Landsat-5 TM and TOPSAR data, with their multichannel information, gave the better segmentation results. The segmentation was difficult for both ERS-l and Radarsat images due to their only single channel information. An improvement was achieved by the incorporation of the textural information where the combined spectral (or SAR backscattering) and textural input yielded lower errors than that of using spectral (or SAR backscattering) or textural data alone. 2003 Thesis http://eprints.utm.my/id/eprint/42622/ http://eprints.utm.my/id/eprint/42622/1/LeeCheeHongMFKKKSA2004.pdf application/pdf en public http://libraryopac.utm.my/client/en_AU/main/search/detailnonmodal/ent:$002f$002fSD_ILS$002f0$002fSD_ILS:356684/one?qu=Comparison+of+segmentation+techniques+remotely+sensed+images+for+land+cover+features masters Universiti Teknologi Malaysia, Faculty of Geoinformation and Real Estate Faculty of Geoinformation and Real Estate
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	G Geography Anthropology Recreation
spellingShingle	G Geography Anthropology Recreation Lee, Ken Yoong Comparison of segmentation techniques remotely sensed images for land cover features
description	This study presents the comparison of edge and region-based segmentation approaches in segmenting linear and polygonal land cover features respectively in optical, single polarization SAR, and multi-polarization SAR images which covered the area of Asajaya, Sarawak and Kuala Nerus, Terengganu. To segment the linear features, the procedures included: edge detection, edge map transformation, edge thinning, and edge linking. From the results obtained, the kernel-based first derivative (i.e. Frei-Chen, Kirsch, Prewitt, and Sobel) gave the better outcomes based on the identification accuracy computed. The segmentation was, however, bounded by two factors: (l) the sensitivity of edge detectors to image texture and (2) the characteristics of input data. For polygonal features, three different region-based segmentors, namely centroid linkage region grower, split-and-merge, and morphological watershed transform, were applied to the following inputs: (1) spectral (or SAR backscattering) data alone, (2) texture data alone, and (3) combined spectral (or SAR backscattering) and textural data. In this study, it was found that the centroid linkage region growing was superior to the split-and-merge and watershed transform. The Landsat-5 TM and TOPSAR data, with their multichannel information, gave the better segmentation results. The segmentation was difficult for both ERS-l and Radarsat images due to their only single channel information. An improvement was achieved by the incorporation of the textural information where the combined spectral (or SAR backscattering) and textural input yielded lower errors than that of using spectral (or SAR backscattering) or textural data alone.
format	Thesis
qualification_level	Master's degree
author	Lee, Ken Yoong
author_facet	Lee, Ken Yoong
author_sort	Lee, Ken Yoong
title	Comparison of segmentation techniques remotely sensed images for land cover features
title_short	Comparison of segmentation techniques remotely sensed images for land cover features
title_full	Comparison of segmentation techniques remotely sensed images for land cover features
title_fullStr	Comparison of segmentation techniques remotely sensed images for land cover features
title_full_unstemmed	Comparison of segmentation techniques remotely sensed images for land cover features
title_sort	comparison of segmentation techniques remotely sensed images for land cover features
granting_institution	Universiti Teknologi Malaysia, Faculty of Geoinformation and Real Estate
granting_department	Faculty of Geoinformation and Real Estate
publishDate	2003
url	http://eprints.utm.my/id/eprint/42622/1/LeeCheeHongMFKKKSA2004.pdf
_version_	1747816814409154560

Comparison of segmentation techniques remotely sensed images for land cover features

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