基于似圓陰影的光學(xué)遙感圖像油罐檢測(cè)

李軒; 劉云清

doi:10.11999/JEIT151334

基于似圓陰影的光學(xué)遙感圖像油罐檢測(cè)

doi: 10.11999/JEIT151334

李軒¹,
劉云清²

2.
(長(zhǎng)春理工大學(xué)電子信息工程學(xué)院長(zhǎng)春 130022) ②(中國(guó)科學(xué)院國(guó)家空間科學(xué)中心復(fù)雜航天系統(tǒng)電子信息技術(shù)重點(diǎn)實(shí)驗(yàn)室北京 100190)

基金項(xiàng)目:

國(guó)家973計(jì)劃(613192)

計(jì)量
- 文章訪問數(shù): 1713
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2015-11-26
- 修回日期: 2016-03-23
- 刊出日期: 2016-06-19

Oil Tank Detection in Optical Remote Sensing Imagery Based on Quasi-circular Shadow

LI Xuan¹,
LIU Yunqing²

2.
(School of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun 130022, China)

Funds:

The National 973 Program of China (613192)

摘要

摘要: 針對(duì)光學(xué)遙感圖像中受陰影干擾的油罐目標(biāo)識(shí)別率低的問題，該文提出一種將改進(jìn)的視覺顯著模型與似圓陰影區(qū)域特征檢測(cè)相結(jié)合的由粗到精的油罐目標(biāo)檢測(cè)方法。首先建立改進(jìn)的視覺顯著模型，將油罐從復(fù)雜背景中粗分離。然后對(duì)分離結(jié)果中由油罐產(chǎn)生的似圓陰影區(qū)域進(jìn)行精檢測(cè)，得到疑似油罐目標(biāo)。再去除陰影，獲得油罐目標(biāo)的初步檢測(cè)結(jié)果。最后基于圖搜索策略及先驗(yàn)知識(shí)，確定油罐目標(biāo)并定位油庫區(qū)域。實(shí)驗(yàn)結(jié)果表明，該方法對(duì)檢測(cè)光學(xué)遙感圖像中存在似圓陰影的油罐目標(biāo)具有較高的魯棒性和準(zhǔn)確率。同時(shí)，在不同環(huán)境的光學(xué)遙感圖像中使用該方法可快速準(zhǔn)確地定位油庫區(qū)域。
- 光學(xué)遙感圖像 /
- 似圓陰影區(qū)域 /
- 視覺顯著模型 /
- 特征檢測(cè) /
- 油罐
Abstract: To deal with the issue of low oil tanks recognition rate in optical remote sensing image, an improved oil tanks detection method is proposed, which is based on the improved visual saliency model and quasi-circular shadow region. Firstly, the oil tanks are separated from the complex background by using the improved visual saliency model. Secondly, the circular shadow regions are finely detected, and the suspected oil tanks are obtained. Then, the shadow region and the preliminary detection result of oil tanks are obtained. Finally, the false oil tank targets are removed and oil depots are determined based on graph search strategy and prior knowledge. The proposed method is robust to the oil tanks in the optical remote sensing images, and can effectively detect the oil tanks in high recognition rate. The experimental results indicate that the proposed algorithm are fast and accurate to detect the oil tanks, which is suitable for optical remote sensing images of different spatial resolutions.
- Optical remote sensing images /
- Quasi-circular shadow region /
- Visual saliency model /
- Feature detection /
- Oil tanks

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參考文獻(xiàn)(21)

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