Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion
Synthetic aperture radar in the application of remote sensing technology is becoming more and more widely because of its all-time and all-weather operation, feature extraction research in high resolution SAR image has become a hot topic of concern. In particular, with the continuous improvement of a...
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2015-06-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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doaj-cd6d5609e5194d1ba5efe84f5ad9a84c2020-11-25T01:45:12ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342015-06-01XL-7/W412112510.5194/isprsarchives-XL-7-W4-121-2015Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted FusionX. Liu0J. X. Zhang1Z. Zhao2A. D. Ma3Shandong Agricultural University, Tai'an, ChinaChinese Academy of surveying and Mapping, Beijing 100830, ChinaChinese Academy of surveying and Mapping, Beijing 100830, ChinaChina University of Geosciences, Hubei Wuhan 430074, ChinaSynthetic aperture radar in the application of remote sensing technology is becoming more and more widely because of its all-time and all-weather operation, feature extraction research in high resolution SAR image has become a hot topic of concern. In particular, with the continuous improvement of airborne SAR image resolution, image texture information become more abundant. It’s of great significance to classification and extraction. In this paper, a novel method for built-up areas extraction using both statistical and structural features is proposed according to the built-up texture features. First of all, statistical texture features and structural features are respectively extracted by classical method of gray level co-occurrence matrix and method of variogram function, and the direction information is considered in this process. Next, feature weights are calculated innovatively according to the Bhattacharyya distance. Then, all features are weighted fusion. At last, the fused image is classified with K-means classification method and the built-up areas are extracted after post classification process. The proposed method has been tested by domestic airborne P band polarization SAR images, at the same time, two groups of experiments based on the method of statistical texture and the method of structural texture were carried out respectively. On the basis of qualitative analysis, quantitative analysis based on the built-up area selected artificially is enforced, in the relatively simple experimentation area, detection rate is more than 90%, in the relatively complex experimentation area, detection rate is also higher than the other two methods. In the study-area, the results show that this method can effectively and accurately extract built-up areas in high resolution airborne SAR imagery.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W4/121/2015/isprsarchives-XL-7-W4-121-2015.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
X. Liu J. X. Zhang Z. Zhao A. D. Ma |
spellingShingle |
X. Liu J. X. Zhang Z. Zhao A. D. Ma Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
X. Liu J. X. Zhang Z. Zhao A. D. Ma |
author_sort |
X. Liu |
title |
Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion |
title_short |
Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion |
title_full |
Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion |
title_fullStr |
Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion |
title_full_unstemmed |
Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion |
title_sort |
built-up areas extraction in high resolution sar imagery based on the method of multiple feature weighted fusion |
publisher |
Copernicus Publications |
series |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
1682-1750 2194-9034 |
publishDate |
2015-06-01 |
description |
Synthetic aperture radar in the application of remote sensing technology is becoming more and more widely because of its all-time
and all-weather operation, feature extraction research in high resolution SAR image has become a hot topic of concern. In particular,
with the continuous improvement of airborne SAR image resolution, image texture information become more abundant. It’s of great
significance to classification and extraction. In this paper, a novel method for built-up areas extraction using both statistical and
structural features is proposed according to the built-up texture features. First of all, statistical texture features and structural features
are respectively extracted by classical method of gray level co-occurrence matrix and method of variogram function, and the
direction information is considered in this process. Next, feature weights are calculated innovatively according to the Bhattacharyya
distance. Then, all features are weighted fusion. At last, the fused image is classified with K-means classification method and the
built-up areas are extracted after post classification process. The proposed method has been tested by domestic airborne P band
polarization SAR images, at the same time, two groups of experiments based on the method of statistical texture and the method of
structural texture were carried out respectively. On the basis of qualitative analysis, quantitative analysis based on the built-up area
selected artificially is enforced, in the relatively simple experimentation area, detection rate is more than 90%, in the relatively
complex experimentation area, detection rate is also higher than the other two methods. In the study-area, the results show that this
method can effectively and accurately extract built-up areas in high resolution airborne SAR imagery. |
url |
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W4/121/2015/isprsarchives-XL-7-W4-121-2015.pdf |
work_keys_str_mv |
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