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A Method for Automatic Infrared Point Target Detection in a Sea Background Based on Morphology and Wavelet Transform

机译:基于形态学和小波变换的海洋背景红外点目标自动检测方法

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A method is developed for the detection and segmentation of spot targets at sea surface. Firstly, the Sea-Sky-Division-Line (SSDL), close to the horizon, is detected by wavelet-transform to mark out the Target Potential Region (TPR), which can reduce the target searching range. A Row average grayscale subtraction (RAGS) operation is employed to correct the blur caused by the non-linearity distribution of the temperature field. To repress the clutter in the background and increase the SNR of the image, a morphology Top-Hat filter is utilized. Then, the image is opening by selecting a proper structuring element to acquire a few potential target points. Through searching the maximal intensity and determining a threshold, most of the false alarms can be eliminated and the doubtful targets can be segmented. When the SSDL is visible, the real point-target can be retained according to the TPR and the false target can be discarded. Under the conditions of invisibility of SSDL for it is outside of the image or it is obscure due to the weather, the segmented target is the real target. The experiment results show that the method can effectively detect and segment infrared point target in complex sea background.
机译:开发了一种用于检测和分割海面斑点目标的方法。首先,通过小波变换检测接近地平线的海天分割线(SSDL),以标记出目标潜在区域(TPR),从而缩小目标搜索范围。行平均灰度减法(RAGS)操作用于校正由温度场的非线性分布引起的模糊。为了抑制背景中的杂波并提高图像的SNR,可使用形态学Top-Hat滤波器。然后,通过选择适当的结构元素以获取一些潜在的目标点来打开图像。通过搜索最大强度并确定阈值,可以消除大多数错误警报,并对可疑目标进行分段。当可以看到SSDL时,可以根据TPR保留真实的点目标,而可以丢弃错误的目标。在SSDL不可见的情况下,因为它在图像之外或由于天气而变得模糊,所以分割后的目标才是真实目标。实验结果表明,该方法可以有效地检测和分割复杂海底红外点目标。

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