DocumentCode
2242986
Title
Texture-Based Remote-Sensing Image Segmentation
Author
Guo, Dihua ; Atluri, Vijayalakshmi ; Adam, Nico
fYear
2005
fDate
6-6 July 2005
Firstpage
1472
Lastpage
1475
Abstract
Typically, high-resolution remote sensing (HRRS) images contain a high level noise as well as possess different texture scales. As a result, existing image segmentation approaches are not suitable to HRRS imagery. In this paper, we have presented an unsupervised texture-based segmentation algorithm suitable for HRRS images, by extending the local binary pattern texture features and the lossless wavelet transform. Our experimental results using USGS 1 ft orthoimagery show a significant improvement over the previously proposed LBP approach
Keywords
feature extraction; geophysical signal processing; image segmentation; image texture; remote sensing; unsupervised learning; wavelet transforms; HRRS; USGS orthoimagery; binary pattern feature; high-resolution remote sensing; image segmentation; lossless wavelet transform; unsupervised texture-based segmentation algorithm; Image segmentation; Lab-on-a-chip; Remote sensing; Tellurium; Tin;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on
Conference_Location
Amsterdam
Print_ISBN
0-7803-9331-7
Type
conf
DOI
10.1109/ICME.2005.1521710
Filename
1521710
Link To Document