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A jigger ship's automatic detection method based on VIIRS DNB data

机译:基于VIIRS DNB数据的跳伞船的自动检测方法

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The Visible Infrared Imaging Radiometer (VIIRS) day/night band (DNB) onboard Suomi National Polar-orbiting Partnership (NPP) satellite offers a wide range of applications at night, ranging from fire detection, meteorological phenomena to observations of anthropogenic light sources. It is becoming a useful tool to monitor and quantify these ships by detecting the light emitted by the lamps. In this study, a threshold-based method is presented to automatically identify the ships. Before detection, several pre-processing steps including contrast enhancement and instrument noise removal are conducted; then the background value is subtracted from the original image to reduce the blurred area around the target, which can further make the gathered ships isolated; In addition, the effects of some interference sources such as ionospheric energetic particles and thin clouds are also taken into consideration for improving the detection rate. Finally, the proposed threshold-based method is applied to the DNB images over study areas in Yellow Sea and Bohai Sea in China. The detection results show that the proposed method can detect more than 81% of ships when comparing with those from Automatic Identification System (AIS).
机译:可见红外成像辐射计(VIIRS)日/夜间乐队(DNB)船上船上国家(DNB)国家极性轨道合作(NPP)卫星在夜间提供广泛的应用,从火灾探测,气象现象到人为光源观察。它正在成为监视和量化这些船只通过检测由灯发射的光来监测和量化这些船舶的有用工具。在该研究中,提出了一种基于阈值的方法以自动识别船只。在检测之前,进行包括对比增强和仪器噪声去除的几个预处理步骤;然后从原始图像中减去背景值以减少目标周围的模糊区域,这可以进一步制造被隔离的聚集的船舶;此外,还考虑了一些干扰源的影响,例如电离层能量粒子和薄云,以提高检测率。最后,将拟议的基于阈值的方法应用于中国在中国黄海和渤海的研究区的DNB图像。检测结果表明,当与自动识别系统(AIS)相比,该方法可以检测超过81%的船舶。

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