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首页> 外文期刊>Journal of the Indian Society of Remote Sensing >Oil Tanks Extraction from High Resolution Imagery Using a Directional and Weighted Hough Voting Method
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Oil Tanks Extraction from High Resolution Imagery Using a Directional and Weighted Hough Voting Method

机译：使用定向加权加权投票方法从高分辨率图像中提取油箱

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摘要

Automatic objects detection, such as oil tanks, is an important application of high resolution satellite image, which can be used in disaster prevention, environment monitoring, and some military tasks. Hough Transform is one of the most commonly used method for circle target detection in the literature. However, complicated details and background in high resolution image make it difficult to find a satisfying edge map, which limits the accuracy of oil tanks extracted by edge based Circular Hough Transform methods. In this paper, we propose a novel process to detect circles directly from the gradient image rather than the edge map. By this way, we avoid the problem of edge extraction. On the other hand, by searching for the most suitable circle center in a buffer region, rather than just selecting the local maximum, we improve the accuracy of circle center location significantly. We have applied this approach to different high resolution satellite images, and find both the completeness and the accuracy of the proposed algorithm superior to the traditional edge based Hough method.
机译：自动目标检测（例如油箱）是高分辨率卫星图像的重要应用，可用于防灾，环境监控和某些军事任务。霍夫变换是文献中最常用的圆形目标检测方法之一。然而，高分辨率图像中复杂的细节和背景使得难以找到令人满意的边缘图，这限制了通过基于边缘的环形霍夫变换方法提取的油箱的精度。在本文中，我们提出了一种直接从梯度图像而不是边缘图检测圆的新颖方法。通过这种方式，我们避免了边缘提取的问题。另一方面，通过在缓冲区中搜索最合适的圆心，而不仅仅是选择局部最大值，我们可以显着提高圆心位置的精度。我们已经将该方法应用于不同的高分辨率卫星图像，并且发现该算法的完整性和准确性均优于传统的基于边缘的Hough方法。

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