Texture-based remote-sensing image segmentation

被引：0
|
作者：
Guo, DH
Atluri, V
Adam, N
机构：
来源：
2005 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME), VOLS 1 AND 2 | 2005年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：1473 / 1476
页数：4
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