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浏览/检索结果: 共8条，第1-8条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 A parameter inversion for sea bridge based on high-resolution polarimetric synthetic aperture radar 期刊论文 ACTA OCEANOLOGICA SINICA, 2016, 卷号: 35, 期号: 7, 页码: 68-75 作者:  Liu Genwang;  Zhang Jie;  Zhang Xi;  Meng Junmin;  Wang Guoyu 收藏  |  浏览/下载：3/0  |  提交时间：2019/08/19 high-resolution PolSAR  sea bridge  parameter inversion  multiband   A parameter inversion for sea bridge based on high-resolution polarimetric synthetic aperture radar 期刊论文 ACTA OCEANOLOGICA SINICA, 2016, 卷号: 35, 期号: 7, 页码: 68-75 作者:  Liu Genwang;  Zhang Jie;  Zhang Xi;  Meng Junmin;  Wang Guoyu 收藏  |  浏览/下载：5/0  |  提交时间：2018/12/07 high-resolution PolSAR  sea bridge  parameter inversion  multiband   Extraction of bridges over water from high-resolution optical remote-sensing images based on mathematical morphology 期刊论文 国际遥感杂志, 2014 Chen, Chao; Qin, Qiming; Zhang, Ning; Li, Jun; Chen, Li; Wang, Jun; Qin, Xuebin; Yang, Xiucheng 收藏  |  浏览/下载：3/0  |  提交时间：2015/11/10 MAN-MADE OBJECTS  MULTISPECTRAL IMAGES  INDEX NDWI  RECOGNITION  INFORMATION  FEATURES   基于地物光谱特征分析的高分辨率遥感图像水上桥梁提取 期刊论文 光谱学与光谱分析, 2013 陈超; 秦其明; 陈理; 王金梁; 刘明超; 温奇 收藏  |  浏览/下载：5/0  |  提交时间：2015/11/11 地物光谱特征 高分辨率遥感图像 水上桥梁提取 数学形态学  Spectral characteristics of ground objects  High-resolution remote sensing image  Extraction of bridge over water  Mathematical morphology   Automatic bridge extraction for optical images (EI CONFERENCE) 会议论文 6th International Conference on Image and Graphics, ICIG 2011, August 12, 2011 - August 15, 2011, Hefei, Anhui, China Gu D.-Y.; Zhu C.-F.; Shen H.; Hu J.-Z.; Chang H.-X. 收藏  |  浏览/下载：16/0  |  提交时间：2013/03/25 This paper describes a novel hierarchy algorithm for extracting bridges over water in optical images. To reduce the omission of bridges by searching the edge  we extract the river regions which the bridges are included in. Firstly  we segment the optical image to get the coarse water bodies using iterative threshold  eliminate the noise regions and add the missing regions based on k-means clustering with texture information and spatial coherence. Then  the blanks are connected based on shape features and candidate bridge regions are segmented from river regions. Finally  the bridges are verified by geometric information and the ubiety between bridges and river. The results show that this approach is efficient and effective for extracting bridges in satellite image from Google Earth and in aerial optical images acquired by unmanned aerial vehicle. 2011 IEEE.   Extraction of bridges over water from IKONOS panchromatic data SCI/SSCI论文 2007 Luo J.; Ming D.; Liu W.; Shen Z.; Wang M.; Sheng H. 收藏  |  浏览/下载：16/0  |  提交时间：2012/06/08 support vector machines  texture classification   Extraction of bridges over water from IKONOS panchromatic data EI期刊论文 2007 Luo J.; Ming D.; Liu W.; Shen Z.; Wang M.; Sheng H. 收藏  |  浏览/下载：14/0  |  提交时间：2012/06/11 Feature extraction  Image classification  Object recognition  Remote sensing  Satellite imagery  Support vector machines   Extraction of bridges over water from IKONOS panchromatic data 期刊论文 International Journal of Remote Sensing, 2007, 卷号: 28, 期号: 16, 页码: 3633-3648 Luo, J.; Ming, D.; Liu, W.; Shen, Z.; Wang, M.; Sheng, H. 收藏  |  浏览/下载：10/0  |  提交时间：2014/12/07