Extraction of Human Settlements from High Resolution Remote Sensing Imagery by Fusing Features of Right Angle Corners and Right Angle Sides

A method for human settlements extraction from high resolution remote sensing imagery using feature-level-based fusion of right-angle-corners and right-angle-sides is proposed in this paper. First, the corners and line segments are detected, the right-angle-corners and right-angle-sides are determin...

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Main Authors: LIN Xiangguo, NING Xiaogang
Format: Article
Language:zho
Published: Surveying and Mapping Press 2017-01-01
Series:Acta Geodaetica et Cartographica Sinica
Subjects:
Online Access:http://html.rhhz.net/CHXB/html/2017-1-83.htm
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spelling doaj-939458b377fd45aa80a6cf6237bbb7fe2020-11-25T01:22:48ZzhoSurveying and Mapping PressActa Geodaetica et Cartographica Sinica1001-15951001-15952017-01-01461838910.11947/j.AGCS.2017.201603892017010389Extraction of Human Settlements from High Resolution Remote Sensing Imagery by Fusing Features of Right Angle Corners and Right Angle SidesLIN Xiangguo0NING Xiaogang1Chinese Academy of Surveying and Mapping, Beijing 100830, ChinaChinese Academy of Surveying and Mapping, Beijing 100830, ChinaA method for human settlements extraction from high resolution remote sensing imagery using feature-level-based fusion of right-angle-corners and right-angle-sides is proposed in this paper. First, the corners and line segments are detected, the right-angle-corners and right-angle-sides are determined by cross verification of the detected corners and line segments, and these two types of features are rasterized. Second, a human settlement index image is built based on the density and distance of the right-angle-corners and right-angle-sides in a local region. Finally, the polygons of human settlements are generated through binary thresholding of the index image, conversion from raster format to vector format, and sieving. Three images are used for testing the proposed method. The experimental results show that our proposed method has higher accuracy than the existed method. Specifically, the correctrate, completeness, and quality of our method is higher 6.76%, 10.12%, 12.14% respectively than the existed method.http://html.rhhz.net/CHXB/html/2017-1-83.htmhigh resolution remote sensing imagehuman settlementHarris cornersline segmentspatial voting
collection DOAJ
language zho
format Article
sources DOAJ
author LIN Xiangguo
NING Xiaogang
spellingShingle LIN Xiangguo
NING Xiaogang
Extraction of Human Settlements from High Resolution Remote Sensing Imagery by Fusing Features of Right Angle Corners and Right Angle Sides
Acta Geodaetica et Cartographica Sinica
high resolution remote sensing image
human settlement
Harris corners
line segment
spatial voting
author_facet LIN Xiangguo
NING Xiaogang
author_sort LIN Xiangguo
title Extraction of Human Settlements from High Resolution Remote Sensing Imagery by Fusing Features of Right Angle Corners and Right Angle Sides
title_short Extraction of Human Settlements from High Resolution Remote Sensing Imagery by Fusing Features of Right Angle Corners and Right Angle Sides
title_full Extraction of Human Settlements from High Resolution Remote Sensing Imagery by Fusing Features of Right Angle Corners and Right Angle Sides
title_fullStr Extraction of Human Settlements from High Resolution Remote Sensing Imagery by Fusing Features of Right Angle Corners and Right Angle Sides
title_full_unstemmed Extraction of Human Settlements from High Resolution Remote Sensing Imagery by Fusing Features of Right Angle Corners and Right Angle Sides
title_sort extraction of human settlements from high resolution remote sensing imagery by fusing features of right angle corners and right angle sides
publisher Surveying and Mapping Press
series Acta Geodaetica et Cartographica Sinica
issn 1001-1595
1001-1595
publishDate 2017-01-01
description A method for human settlements extraction from high resolution remote sensing imagery using feature-level-based fusion of right-angle-corners and right-angle-sides is proposed in this paper. First, the corners and line segments are detected, the right-angle-corners and right-angle-sides are determined by cross verification of the detected corners and line segments, and these two types of features are rasterized. Second, a human settlement index image is built based on the density and distance of the right-angle-corners and right-angle-sides in a local region. Finally, the polygons of human settlements are generated through binary thresholding of the index image, conversion from raster format to vector format, and sieving. Three images are used for testing the proposed method. The experimental results show that our proposed method has higher accuracy than the existed method. Specifically, the correctrate, completeness, and quality of our method is higher 6.76%, 10.12%, 12.14% respectively than the existed method.
topic high resolution remote sensing image
human settlement
Harris corners
line segment
spatial voting
url http://html.rhhz.net/CHXB/html/2017-1-83.htm
work_keys_str_mv AT linxiangguo extractionofhumansettlementsfromhighresolutionremotesensingimagerybyfusingfeaturesofrightanglecornersandrightanglesides
AT ningxiaogang extractionofhumansettlementsfromhighresolutionremotesensingimagerybyfusingfeaturesofrightanglecornersandrightanglesides
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