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	Research on infrared dim-point target detection and tracking under sea-sky-line complex background (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China 作者: Dong Y.-X.; Zhang H.-B.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：111/0 \| 提交时间：2013/03/25 Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties.There are some traditional point target detection algorithms such as adaptive background prediction detecting method. When background has dispersion-decreasing structure the traditional target detection algorithms would be more useful. But when the background has large gray gradient such as sea-sky-line sea waves etc.The bigger false-alarm rate will be taken in these local area.It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature in our opinion from the perspective of mathematics the detection of dim-point targets in image is about singular function analysis.And from the perspective image processing analysis the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection its essence is a separation of target and background of different singularity characteristics.The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore the purpose of the image preprocessing is to reduce the effects from noise also to raise the SNR of image and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics the median filter is used to eliminate noise improve signal-to-noise ratio then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
	OIL SLICK SPOT DETECTION USING K-DISTRIBUTION MODEL OF THE SEA BACKGROUND 会议论文 OAI收割 2009 Ieee International Geoscience and Remote Sensing Symposium, Vols 1-5, New York Li, Hong-zhong; Wang, Chao; Zhang, Hong; Wu, Fan; Li, Jilong 收藏 \| 浏览/下载：32/0 \| 提交时间：2014/12/07 oil spill dark spot detection Sea clutter kappa -distribution model SPILL DETECTION SAR IMAGES
	Research on tracking approach to low-flying weak small target near the sea (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Xue X.-C. 收藏 \| 浏览/下载：33/0 \| 提交时间：2013/03/25 Automatic target detection is very difficult in complicate background of sea and sky because of the clutter caused by waves and clouds nearby the sea-level line. In this paper in view of the low-flying target near the sea is always above the sea-level line we can first locate the sea-level line and neglect the image data beneath the sea-level line. Thus the noise under the sea-level line can be suppressed and the executive time of target segmentation is also much reduced. A new method is proposed which first uses neighborhood averaging method to suppress background and enhance targets so as to increase SNR and then uses the multi-point multi-layer vertical Sobel operator combined with linear least squares fitting to locate the sea-level line lastly uses the centroid tracking algorithm to detect and track the target. In the experiment high frame rate and high-resolution digital CCD camera and high performance DSP are applied. Experimental results show that this method can efficiently locate the sea-level line on various conditions of lower contrast and eliminate the negative impact of the clutter caused by waves and clouds and capture and track target real-timely and accurately.