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	Adaptive Background Clutter Mitigation for Millimeter Wave MIMO Imaging 期刊论文 OAI收割 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 16 作者: Tian, Xianzhong; Wang, Zhongmin; Chang, Tianying; Cui, Hong-Liang \| 收藏 \| 浏览/下载：33/0 \| 提交时间：2022/08/22 Clutter Manganese Imaging Radar imaging MIMO communication Antenna arrays Radar Adaptive antenna array background clutter millimeter wave multiple-input multiple-output (MIMO)
	Small target detection based on reweighted infrared patch-image model 期刊论文 OAI收割 IET IMAGE PROCESSING, 2018, 卷号: 12, 期号: 1, 页码: 70-79 作者: Guo, Jun; Wu, Yiquan; Dai, Yimian \| 收藏 \| 浏览/下载：73/0 \| 提交时间：2018/12/12 Object Detection Infrared Imaging Principal Component Analysis Small Target Detection Reweighted Infrared Patch-image Model Infrared Small Target Detection Sparse Background Edges Background Estimation Reweighted Nuclear Norm Nontarget Sparse Points Reweighted Robust Principal Component Analysis Problem Inexact Augmented Lagrangian Multiplier Method Background Clutter Suppression Reweighted l(1) Norm
	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：108/0 \| 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).
	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：32/0 \| 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.
	High-accuracy real-time automatic thresholding for centroid tracker (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Zhang Y. 收藏 \| 浏览/下载：37/0 \| 提交时间：2013/03/25 Many of the video image trackers today use the centroid as the tracking point. In engineering we can get several key pairs of peaks which can include the target and the background around it and use the method of Otsu to get intensity thresholds from them. According to the thresholds it give a great help for us to get a glancing size a target's centroid is computed from a binary image to reduce the processing time. Hence thresholding of gray level image to binary image is a decisive step in centroid tracking. How to choose the feat thresholds in clutter is still an intractability problem unsolved today. This paper introduces a high-accuracy real-time automatic thresholding method for centroid tracker. It works well for variety types of target tracking in clutter. The core of this method is to get the entire information contained in the histogram we can gain the binary image and get the centroid from it. To track the target so that we can compare the size of the object in the current frame with the former. If the change is little such as the number of the peaks the paper also suggests subjoining an eyeshot-window we consider the object has been tracked well. Otherwise their height just like our eyes focus on a target if the change is bigger than usual position and other properties in the histogram. Combine with this histogram analysis we will not miss it unless it is out of our eyeshot we should analyze the inflection in the histogram to find out what happened to the object. In general the impression will help us to extract the target in clutter and track it and we will wait its emergence since it has been covered. To obtain the impression what we have to do is turning the analysis into codes for the tracker to determine a feat threshold. The paper will show the steps in detail. The paper also discusses the hardware architecture which can meet the speed requirement. the paper offers a idea comes from the method of Snakes