Title :
Extracting Building Unit Number Information from High Resolution SAR Images with Regression Model
Author :
Su, Caixia ; Cao, Yongfeng ; Liang, Jianjuan
Author_Institution :
Sch. of Math. & Comput. Sci., Guizhou Normal Univ., Guiyang, China
Abstract :
High resolution Synthetic Aperture Radar (SAR) sensor, which delivers images with metric or sub-metric resolution, makes it possible to extract detailed urban information. An effective method for extracting building unit number information from high resolution SAR images is proposed. In this method, a combination of intensity threshold and morphological operations are firstly used to detect buildings in SAR imagery. Then a regression function that describes the obvious correlativity existed between the features of the detected bright patch and the real number of buildings in the bright patch are modeled to predict the building number information in any region. The experiment on a TerraSAR_X image covering part of Wuhan city of China with spatial resolution 1.25×1.25m per pixel shows that the proposed method can get much more accurate building unit number information than using the number of the detected bright patches as the number of building units directly.
Keywords :
radar imaging; radar resolution; regression analysis; synthetic aperture radar; TerraSAR_X image; bright patch; building unit number information extraction; high resolution SAR images; intensity threshold; metric resolution; morphological operations; regression model; submetric resolution; synthetic aperture radar sensor; urban information; Buildings; Data mining; Equations; Feature extraction; Image resolution; Mathematical model; Synthetic aperture radar; Building Unit Number; High Resolution Synthetic Aperture Radar (SAR) Image; Regression analysis;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-2406-9
DOI :
10.1109/ICCIS.2012.153