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Ship Detection from Optical Satellite Image using Optical Flow and Saliency

机译:使用光学流动和显着性从光学卫星图像检测

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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:本文介绍了使用光学卫星图像的光流量和显着性方法的船舶检测的有效方法,该方法可以能够在复杂的动态海背景中识别多个船舶目标,并与传统方法相比,降低假阳性率。在本文中,通过经典光学流量方法突出显示图像中的移动目标,通过组合最先进的显着性方法来抑制动态波。我们充分利用图像的低级(大小,颜色等)和高级(相邻帧信息等)的图像,这可以适应不同的动态背景情况。与现有方法相比,实验结果表明了具有高性能的提出方法的鲁棒性。

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