...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Image Processing, IET >Target detection of hyperspectral image based on spectral saliency
【24h】

Target detection of hyperspectral image based on spectral saliency

机译：基于光谱显着性的高光谱图像目标检测

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Target detection of hyperspectral image (HSI) is a research hotspot in the field of remote sensing. It is of particular importance in many domains, especially in military application. Unsupervised target detection is usually more difficult because there is no prior information about target. Traditional algorithms exploit spectral information, only. This study introduces the idea of saliency detection from the visual technique into HSI processing domain and proposes a novel approach named spectral saliency target detection (SSD). It establishes a novel salient model, which utilises both spatial saliency and spectral saliency. In the framework of SSD, it combines the model with spectral matching algorithm to make it perform well even in situations where the target is concealed and small. A HSI set comprised of eight different scenes with complex background is setup to evaluate the performance of the proposed algorithm. The final visible detection results demonstrate that the SSD algorithm outperforms the others. The receiver operation characteristic (ROC) curve and area under the ROC curve are applied to evaluate the results. The proposed algorithm shows superior and stable performance.
机译：高光谱图像（HSI）的目标检测是遥感领域的研究热点。在许多领域，特别是在军事应用中，它尤其重要。无监督目标检测通常更加困难，因为没有关于目标的先验信息。传统算法仅利用频谱信息。这项研究将视觉技术的显着性检测思想引入了HSI处理领域，并提出了一种称为光谱显着性目标检测（SSD）的新方法。建立了利用空间显着性和频谱显着性的新型显着模型。在SSD的框架中，它将模型与光谱匹配算法结合在一起，即使在目标被遮盖且很小的情况下，也能表现良好。建立由八个具有复杂背景的不同场景组成的HSI集，以评估所提出算法的性能。最终的可见检测结果表明，SSD算法优于其他算法。接收器工作特性（ROC）曲线和ROC曲线下的面积用于评估结果。所提出的算法表现出优越而稳定的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号