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Ship Detection from Optical Satellite Image using Optical Flow and Saliency

机译:使用光流和显着度从光学卫星图像进行船舶检测

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This paper present an effective method for ship detection using optical flow and saliency methods from optical satellite images, which can be able to identify more than one ship targets in the complex dynamic sea background and succeeds to reduce the false positive rate compared to traditional methods. In this paper, moving targets in the image are highlighted through the classical optical flow method, and the dynamic waves are restrained by combining the state-of-art saliency method. We make the best of the low-level (size, color, etc.) and high-level (adjacent frames information, etc.) features of image, which can adapt to different dynamic background situation. Compared to existing method, experimental results demonstrate the robustness of the proposed method with high performance.
机译:本文提出了一种有效的利用光学流动和显着性方法从光学卫星图像进行船舶检测的方法,该方法能够在复杂的动态海洋背景下识别多个船舶目标,并且与传统方法相比,能够成功减少误报率。在本文中,通过经典的光流方法突出显示了图像中的运动目标,并结合了最新的显着性方法来抑制动态波。我们充分利用图像的低级(尺寸,颜色等)和高级(相邻的帧信息等)特征,这些特征可以适应不同的动态背景情况。与现有方法相比,实验结果证明了该方法具有较高的鲁棒性。

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