SDBD: A Hierarchical Region-of-Interest Detection Approach in Large-Scale Remote Sensing Image
SDBD: A Hierarchical Region-of-Interest Detection Approach in Large-Scale Remote Sensing Image
复制标题
SDBD：大规模遥感图像中的分层感兴趣区域检测方法
DOI：
10.1109/lgrs.2017.2672560
复制
发表时间：
2017-03
影响因子：
4.8
通讯作者：
Zhang Ye
中科院分区：
文献类型：
--
作者：
Li Tong;Zhang Junping;Lu Xiaochen;Zhang Ye
Region-of-interest (ROI) detection techniques are of great importance in the analysis of remote sensing images, especially in target detection, since the size of the image to be dealt with grows substantially with the improvement of spatial resolution. Most of current studies are not aiming at the specific type of object area detection, and the processed images are rather small compared to the size of the raw data acquired by high-resolution satellite. In this letter, a hierarchical task-driven ROI detection method, based on saliency and density, is proposed to address the detection of the potential object areas in large-scale remote sensing images. The proposed saliency and density-based detection method (SDBD) integrates bottom–up and top–down strategies, where the saliency-based multilevel histogram contrast is presented in the bottom–up phase to obtain the preliminary regions, while the centroid density distribution index (CDDI) is defined in the top–down scheme to refine the previous results. Specifically, superpixel segmentation is introduced in this letter to narrow down the ROI candidates. SDBD is capable of extracting ROI of different objects by adjusting the threshold of CDDI. The experiments are conducted on two data sets to extract ROIs of storage tanks and residence. Experimental results demonstrate that the proposed method is effective in identifying ROI in large-scale data.
登录
查看更多内容
影响因子：
10.6
作者：
Zhicheng Li;L. Itti
通讯作者：
Zhicheng Li;L. Itti
DOI：
10.1109/jstars.2014.2319736
发表时间：
2014-05
影响因子：
5.5
作者：
Li-bao Zhang;Kaina Yang;Hao Li
通讯作者：
Li-bao Zhang;Kaina Yang;Hao Li
法向提升小波变换显着性分析遥感图像感兴趣区域提取
影响因子：
6
作者：
Zhang Libao;Chen Jie;Qiu Bingchang
通讯作者：
Qiu Bingchang
DOI：
10.1109/tpami.2015.2392769
发表时间：
2015-10
影响因子：
23.6
作者：
Zhiyuan Shi;Timothy M. Hospedales;T. Xiang
通讯作者：
Zhiyuan Shi;Timothy M. Hospedales;T. Xiang
DOI：
10.1109/34.730558
发表时间：
1998-11-01
影响因子：
23.6
作者：
Itti, L;Koch, C;Niebur, E
通讯作者：
Niebur, E