scholarly journals Classification of high resolution imagery based on fusion of multiscale texture features

2014 ◽  
Vol 17 ◽  
pp. 012217 ◽  
Author(s):  
Jinxiu Liu ◽  
Huiping Liu ◽  
Ying Lv ◽  
Xiaojuan Xue
Keyword(s):  
High Resolution ◽  
Texture Features ◽  
High Resolution Imagery

Rule-based classification of high-resolution imagery over urban areas in New York City

2013 ◽  
Vol 28 (6) ◽  
pp. 527-545 ◽  
Author(s):  
Sunil Bhaskaran ◽  
Eric Nez ◽  
Karolyn Jimenez ◽  
Sanjiv K. Bhatia
Keyword(s):  
New York ◽  
New York City ◽  
High Resolution ◽  
York City ◽  
Urban Areas ◽  
Rule Based ◽  
High Resolution Imagery

scholarly journals AUTOMATIC EXTRACTION OF BUILDING OUTLINE FROM HIGH RESOLUTION AERIAL IMAGERY

2016 ◽  
Vol XLI-B3 ◽  
pp. 419-423 ◽  
Author(s):  
Yandong Wang
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
Automatic Generation ◽  
Aerial Imagery ◽  
Building Detection ◽  
New Approach ◽  
Building Roof ◽  
High Resolution Imagery ◽  
Point Cloud Classification

In this paper, a new approach for automated extraction of building boundary from high resolution imagery is proposed. The proposed approach uses both geometric and spectral properties of a building to detect and locate buildings accurately. It consists of automatic generation of high quality point cloud from the imagery, building detection from point cloud, classification of building roof and generation of building outline. Point cloud is generated from the imagery automatically using semi-global image matching technology. Buildings are detected from the differential surface generated from the point cloud. Further classification of building roof is performed in order to generate accurate building outline. Finally classified building roof is converted into vector format. Numerous tests have been done on images in different locations and results are presented in the paper.

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