Title :
Building surface texture segmentation in urban remote sensing image using improved ORTSEG algorithm
Author :
Shupei Deng;Ye Zhang;Shu Tian
Author_Institution :
Dept. of Information Engineering, Harbin Institute of Technology, Harbin, China
fDate :
7/1/2015 12:00:00 AM
Abstract :
Texture segmentation is a critical step in building-based analysis in urban remote sensing images to obtain more detail information for further applications. Most existing segmentation algorithms rely on region or edge information to segment, which failed to segment building surfaces with almost same texture and unclear edge between the surfaces. Therefore, in order to solve this challenging task, based on the ORTSEG algorithm in Michael T. McCann´s paper, an improved ORTSEG algorithm is proposed, in which, a sparse non-negative matrix factorization (SNMF) is used for the optimization. The final segmentation results show the superiority of this improved ORTSEG algorithm.
Keywords :
"Image segmentation","Buildings","Histograms","Surface texture","Remote sensing","Algorithm design and analysis","Signal processing algorithms"
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
Electronic_ISBN :
2153-7003
DOI :
10.1109/IGARSS.2015.7326789