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确定区分星点与背景的阈值是星空图像处理的重要环节.介绍了根据背景灰度统计特征确定阈值的算法,根据星空图像灰度直方图的走势,提出一种基于灰度直方图的阈值算法;通过对实际拍摄大视场星图的处理,基于统计的阈值容易将亮背景中的亮噪声误认为星点提取,而基于直方图的阈值能够滤除这些噪点;针对星图中星点亮度不一的情况,提出在全局阈值... 相似文献
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乔小燕 《中国海洋大学学报(自然科学版)》2013,(4):117-122
为有效地提取甲藻生物形态学特征,提出一种自动分割藻种顶刺细节特征的形态学方法,该方法首先将目标旋转至其主轴方向,引入了像素宽度的概念,以藻种目标像素宽度直方图和面积分布为判别依据,自动判定最佳结构元尺寸,最后联合滤波、区域归并等形态学操作提取顶刺区域。实验证明,该算法针对不同甲藻细胞目标可自动计算最佳结构元素大小,精确提取顶刺区域,具有精度高、速度快的优点。 相似文献
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《海洋湖沼通报》2015,(4)
与单极化SAR(Synthetic Aperture Radar)相比,全极化SAR图像中不仅包含散射目标的几何特征和后向散射特征,还包含散射目标的极化特征。因此,基于极化特征的SAR图像分类能够更全面地描述海面目标的物理特性。单次反射特征值相对差异度(Single Bounce Eigenvalue Relative Difference,SERD)能够比较单次散射机制的相对大小,并且可以反映散射表面的粗糙度情况。而海面油膜的存在抑制了海面的短重力波和毛细波,改变了海表面的粗糙度。基于此,本文将SERD应用到海面溢油检测中。利用两景Radarsat-2全极化SAR数据对比分析了SERD与极化散射熵的溢油检测效果,实验发现:(1)SERD能够较好地区分溢油与海水。(2)对原油而言,SERD的油水对比度与极化散射熵的油水对比度在数值上差异较小;对生物油膜而言,SERD的油水对比度在数值上远小于极化散射熵。利用这一特性,SERD在区分生物油膜与原油方面更具优势。 相似文献
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图象中目标具有相似灰度特征,在分割中,我们应考虑区域的整体灰度以及相邻象素灰度的变化,它们依靠于范围参数ε和毗邻参数δ。本文介绍了灰度图象的(ε,δ)连续区域及其模糊边缘测度,提出了通过相对模糊边缘度调整(ε,δ)参数,利用(ε,δ)目标连接集分割图象的一种新算法。实验结果表明该算法分割效果较好,提取边缘精度较高。 相似文献
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基于声信标信号特征的快速识别技术、远距离微弱信号的快速定位技术、空域时域组合的多目标分辨技术,研发了基于圆型基阵的水下声信标搜寻仪"天科寻海一号"。通过消声水池、海上现场等试验,对其各项指标和整体性能进行了测试。该设备探测距离达3 000 m、方向分辨力达0.5°,具备同时搜寻多个声信标的能力。通过实时交会定位方法,可对大面积海域进行快速搜索及准确定位,具有重要的工程应用价值。 相似文献
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基于单矢量水听器四种方位估计方法 总被引:13,自引:0,他引:13
单矢量水听器能同时拾取声场的声压和振速信息,可以估计目标方位。根据不同的噪声背景和信号形式,单矢量水听器有多种方位估计方法。平均声强器的处理方法能很好地抗各向同性的非相干干扰;线谱方位估计能有效检测辐射线谱信号的目标,并进行目标方位估计。当宽带信号中存在线谱相干干扰,以及线谱信号被宽带相干噪声干扰时,上述两种方法不能检测目标。为解决这个问题,新提出了直方图和加权直方图两种方法,直方图方位估计法能抗强线谱相干干扰,并能区分含线谱的多目标;加权直方图方位估计法能从宽带相干干扰中检测目标,估计目标方位。并着重介绍了后两种方法的原理,对四种方法进行了计算机仿真,并用海试结果验证了上述结论。 相似文献
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An automatic approach to the detection and extraction of mine features in sidescan sonar 总被引:6,自引:0,他引:6
Mine detection and classification using high-resolution sidescan sonar is a critical technology for mine counter measures (MCM). As opposed to the majority of techniques which require large training data sets, this paper presents unsupervised models for both the detection and the shadow extraction phases of an automated classification system. The detection phase is carried out using an unsupervised Markov random field (MRF) model where the required model parameters are estimated from the original image. Using a priori spatial information on the physical size and geometric signature of mines in sidescan sonar, a detection-orientated MRF model is developed which directly segments the image into regions of shadow, seabottom-reverberation, and object-highlight. After detection, features are extracted so that the object can be classified. A novel co-operating statistical snake (CSS) model is presented which extracts the highlight and shadow of the object. The CSS model again utilizes available a priori information on the spatial relationship between the highlight and shadow, allowing accurate segmentation of the object's shadow to be achieved. 相似文献
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基于MRF场的侧扫声呐图像分割方法 总被引:1,自引:0,他引:1
为了利用侧扫声呐进行水下目标自动探测和识别,首先必须将声呐图像分为目标高亮区、海底混响区和目标阴影区.由于声呐图像有强背景噪声,传统的图像分割方法显得无能为力,故采用基于MRF场的图像分割方法来准确地分割.根据侧扫声呐目标的成像特点,建立了分割的约束条件;利用阴影与目标的灰度均值比很小这一特点进行初始分割,然后根据分割后目标与阴影的宽度差来剔除虚假目标,由初始分割的结果求得MRF模型初始参数,再采用迭代条件估计得到最终的模型参数和准确的分割结果.由于考虑了相邻像素间的依赖关系,具有抗噪性强、分割效果好的优点,从理论上说是合理的.实测数据分析也证明了这种算法的优越性. 相似文献
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A new pattern-recognition algorithm detects approximately 90% of the mines hidden in the Coastal Systems Station Sonar0, 1, and 3 databases of cluttered acoustic images, with about 10% false alarms. Similar to other approaches, the algorithm presented here includes processing the images with an adaptive Wiener filter (the degree of smoothing depends on the signal strength in a local neighborhood) to remove noise without destroying the structural information in the mine shapes, followed by a two-dimensional FIR filter designed to suppress noise and clutter, while enhancing the target signature. A double peak pattern is produced as the FIR filter passes over mine highlight and shadow regions. Although the location, size, and orientation of this pattern within a region of the image can vary, features derived from higher order spectra (HOS) are invariant to translation, rotation, and scaling, while capturing the spatial correlations of mine-like objects. Classification accuracy is improved by combining features based on geometrical properties of the filter output with features based on HOS. The highest accuracy is obtained by fusing classification based on bispectral features with classification based on trispectral features. 相似文献
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S. N. Kulichkov I. P. Chunchuzov O. I. Popov 《Izvestiya Atmospheric and Oceanic Physics》2010,46(1):60-68
The results of simulating the influence of an atmospheric fine structure on the characteristics of acoustic signals propagating
throughout the atmosphere for long distances from their sources are presented. A numerical model of an atmospheric fine inhomogeneous
structure within the height range z = 20…120 km is proposed to perform calculations. This model and its numerical parameters are based on the current notions
of the formation of an atmospheric fine structure due to internal gravity waves. The numerical calculations were performed
using the parabolic-equation method. A spatial structure of the acoustic field and the structure of an acoustic signal at
long distances from a pulsed source were calculated. It is shown that the presence of an atmospheric fine structure results
in a scattering of acoustic signals and their recording in the geometric shadow region. The results of calculations of signal
forms are in a satisfactory agreement with data on signals recorded in the geometric shadow region which is formed at a distance
of about 300 km from an experimental explosion. 相似文献
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针对侧扫声纳图像目标边缘检测困难的问题,利用二维离散小波变换对侧扫声纳(SSS)声图进行多分辨率分析,对大尺度分解的小波系数进行非极大值抑制,并重构小尺度上的低频分量。联合各尺度上的低频分量,构建SSS声图像素点处特征向量,构成其特征空间,对特征空间进行主成分分析,压缩其维数,并对压缩后的特征向量进行K-均值聚类分析,提取类间边缘线。利用含有沉船的SSS声图,并在其均质区域内加入目标与声影进行验证实验。该方法在实验中边缘检测准确率为0.90,表明该方法的有效性。 相似文献
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三维激光点云数据具有精度高、数据获取高效、几何信息丰富的优势,在地形数据获取方面起到了越来越重要的作用。但在实际的外业测量中,由于视场角限制,一般都难以获取待测物体完整的点云数据,发生数据缺失现象。而根据摄影测量技术生成密集的影像点云,能获取复杂区域的测量数据。针对三维激光点云数据外业采集缺失的状况,结合影像密集点云特征,提出了一种加入动态迭代因子和分步最优求解尺度的改进尺度迭代最近点(scaling iterative closest point, SICP)算法,对影像点云与三维激光点云进行配准研究。实验结果表明:基于改进的SICP算法提高了影像点云与三维激光点云的配准精度、减少了迭代次数,能有效解决不同源平台获取的点云数据融合问题。 相似文献
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This paper presents a neural-network-based system to detect small man-made objects in sequences of sector-scan sonar images created using signals of various pulse lengths. The detection of such objects is considered out to ranges of 150 m by using an experimental sector-scan sonar system mounted on a vessel. The sonar system considered in this investigation has three modes of operation to create images over ranges of 200, 400, and 800 m from the vessel using acoustic pulses of a different duration for each mode. After an initial cleaning operation performed by compensating for the motion of the vessel, the imagery is segmented to extract objects for analysis. A set of 31 features extracted from each object is examined. These features consist of basic object size and contrast features, shape moment-based features, moment invariants, and features extracted from the second-order histogram of each object. Optimal sets of 15 features are then selected for each mode and over all modes using sequential forward selection (SFS) and sequential backward selection (SBS). These features are then used to train neural networks to detect man-made objects in each sonar mode. By the addition of a feature describing the sonar's mode of operation, a neural network is trained to detect man-made objects in any of the three sonar modes. The multimode detector is shown to perform very well when compared with detectors trained specifically for each sonar mode setting. The proposed detector is also shown to perform well when compared to a number of statistical detectors based on the same set of features. The proposed detector achieves a 92.4% probability of detection at a mean false-alarm rate of 10 per image, averaged over all sonar mode settings. 相似文献