共查询到18条相似文献,搜索用时 171 毫秒
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针对复杂的自然背景下的运动目标检测,提出了一种基于分形特征的运动目标检测算法;该算法利用目标的分形维数与自然背景分形维数的差异将目标从背景检测出来;首先应用改进的地毯覆盖法快速得到图像的分形维数,然后通过比较邻域之间分形维数的相互关系进行目标检测;实验结果表明,该方法能对复杂背景下的运动目标进行检测,由于采用分块求分形特征的方法,能有效地减少搜索目标所带来的计算量,算法过程简单、检测速度快、检测结果精确,目标与背景对比度的变化对检测结果几乎没有影响, 且噪声对该算法的检测结果影响较小;在运动目标实时检测问题上有着很好的实用价值和应用前景。 相似文献
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高光谱数据具有图谱合一和数据量大的特点,数据降维是主要的研究方向。波段选择和特征提取是目前高光谱降维的主要方法,就高光谱数据图像岩性特征提取的方法进行了试验和探讨。基于高光谱影像的自相似特征, 探索了分形信号算法在CASI高光谱数据岩性特征提取上的应用研究。以CASI高光谱影像数据为研究对象, 将基于地毯的方法进行修正后用于计算高光谱影像中每一像元的分形信号值。试验结果表明, 与其他分类算法相比分形信号算法增强高光谱图像的影像特征从另一个侧面更细致的描述了不同光谱的可区分性。分形信号影像在一定程度上可以更好地突出基岩裸露地区岩性特征, 从而可以实现影像地表岩性特征提取的目的。原始光谱曲线自身形态特征、初始尺度的选择以及迭代步长等对分形信号和分形特征尺度均有影响。目前,光谱曲线的分形信号特征研究还不多,对其物理意义和定量分析尚需要深入研究。 相似文献
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鉴于红外装甲目标检测中红外图像对比度低、背景复杂,导致图像的信噪比低而难于进行目标的检测,提出一种基于小波和改进的分形理论相结合的背景抑制方法。针对红外图像呈现的相关性强的特点,利用小波分析将图像中的低频缓变背景滤除,得到包含目标和强边缘杂波的图像;又由于目标分形维数对尺度的敏感程度高于边缘杂波的分形维数,提出通过计算图像在不同尺度内不规则因子的变化率来进一步抑制背景中的边缘杂波。实验表明:该算法能显著提高图像的信噪比(信噪比增益在2左右),对背景边缘有很好的抑制效果。 相似文献
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主要研究了分段分数布朗运动(PFBM)模型在雷达海杂波分形建模中的应用.由于自然界和人造系统中研究对象不具有数学上完美的分形特性, 从而研究对象的分形特性无法在整个尺度区间上成立, 传统上, 海杂波的单一分形模型仅利用无标度区间内海杂波的自相似信息进行参数估计, 并没有考虑海杂波在无标度区间以外的尺度下所包含的信息.分段分数布朗运动从频域角度对海杂波频谱进行分段描述, 对应到时域即从粗略尺度和精细尺度两方面描述海杂波时间序列.结合海杂波产生的物理背景, 该模型可以为海杂波时间序列在粗略尺度和精细尺度下表现出的不同粗糙度提供机理性解释.在此基础上, 还研究了具有不同多普勒频率的运动目标对海杂波的影响, 结果表明运动目标对粗略尺度和精细尺度下海杂波的影响程度是不同的. 相似文献
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Tomography Formula for Biochemical Imaging of Thin Tissue with Diffuse-Photon Density Waves
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Artificial object detection
and segmentation in natural background are key points of pattern recognition and computer
vision.The effect of complex texture of natural background and other factors,make it
difficult to segment artificial object from natural background.In this paper,an algorithm
based on watershed transform and regional fractal texture analysis is proposed to detect
and segment artificial object from natural background. 相似文献
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针对海杂波背景下小目标检测对海情依赖性强的问题, 本文采用分数布朗运动模型对实测海杂波建模, 结合多重分形去势波动分析法确定分形参数, 分析了海杂波的单尺度、多重分形特性. 在单尺度分形的基础上, 利用表征海杂波分形特征的分数维和Hurst指数构建了分形差量, 提出了基于分形差量的小目标检测方法;在多重分形基础上, 比较了两种海杂波的高尺度多重分形特性. 结果表明, 当尺度q > 10时, 纯海杂波的多重分形参数H(q) < 0, 而存在小目标的H(q) > 0, 此差异性为高尺度分形参数的海杂波背景小目标检测提供了判定依据. 所研究的两种方法均能实现不同海情下的小目标检测. 相似文献
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Due to the complexity of its radiated sound, ship recognition is difficult. Fractal approaches are proposed in this study, including fractal Brownian motion based analysis, fractal dimension analysis, and wavelet analysis, to augment existing feature extraction methods that are based on spectrum analysis. Experimental results show that fractal approaches are effective. When used to augment two traditional features, line and average spectra, fractal approaches led to better classification results. This implies that fractal approaches can capture some information not detected by traditional approaches alone. 相似文献
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《Physics of life reviews》2007,4(1):1-36
Natural computing is a terminology introduced to encompass three classes of methods: (1) those that take inspiration from nature for the development of novel problem-solving techniques; (2) those that are based on the use of computers to synthesize natural phenomena; and (3) those that employ natural materials (e.g., molecules) to compute. The main fields of research that compose these three branches are the artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, fractal geometry, artificial life, DNA computing, and quantum computing, among others. This paper provides an overview of the fundamentals of natural computing, particularly the fields listed above, emphasizing the biological motivation, some design principles, their scope of applications, current research trends and open problems. The presentation is concluded with a discussion about natural computing, and when it should be used. 相似文献
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白茎绢蒿是一种广泛分布于新疆富蕴县各个矿区的一种植物。在矿区进行矿产勘查时,由于植物等障碍信息的存在,传统的勘查方法已经难以发挥作用,急需一些新方法、新思路。遥感植物地球化学方法可以巧妙地利用植物这一天然的信息源,把植物从障碍信息转换为了有用信息。帮助人们快速、经济地获取植物屏障下的矿产有用信息。由于其具有大面积、快速、无损性等优点,受到了越来越多学者的关注,成为当下的研究热点。近些年虽然有学者综合考虑“吸收系数”和“衬度系数”这两个指标,证明了白茎绢蒿是对隐伏矿床的勘查具有较好指示性作用的植物,生在在矿床上部的植物可以较好的吸收土壤中的成矿元素,在其体内形成地球化学异常,相比于其他植物异常信息更加清晰可见。但是目前没有人研究是否可以从光谱的角度来发现白茎绢蒿体内的地球化学异常,进而为隐伏矿床的勘查提供参考。因此,本研究首次尝试从白茎绢蒿的光谱信息中寻找出与地球化学异常密切相关的特征波段或者特征值, 然后构建基于植物光谱的隐伏矿床预测模型。采取的方法是首先利用ASD FieldSpec3 型光谱仪分别对生长在矿床上部和背景区的植物进行光谱测定,然后从原始光谱、一阶导数光谱、二阶导数光谱、一阶导数的分形维数、二阶导数的分形维数五个层面对生长在这两个区域的植物光谱进行对比分析,最终优选出了10个差异显著的特征波段,分别为:R′824,R′834,R′1 533,R′1 573,R′1 633,R′1 643,R″1 284,R″1 703,一阶导数的分形维数以及二阶导数的分形维数。这些特征波段可以作为植物地区寻找隐伏矿床的植物地球化学标志。以优选出的10个特征波段作为输入参数,分别用随机森林 (RF)和偏最小二乘-支持向量机(PLS-SVM)构建了基于植物光谱数据的隐伏矿床预测模型。结果表明:(1)两种模型均可以取得较好的效果,但是相比于随机森林模型,偏最小二乘-支持向量机模型具有更好的鲁棒性,泛化能力也更强;(2)利用植物的光谱异常寻找隐伏矿床具有较大的潜力,因为相比于传统方法,更加简单、快速。课题组已经利用动力三角翼和HySpex成像高光谱传感器构建了“超低空探测平台”,可以实现对地“亚米级”的观测。但是如何有效的解决“空间尺度”和“光谱尺度”问题,如何把地面试验场建立的模型更好的应用于超低空探测平台,实现研究区大面积地、快速地植物异常信息提取将是我们下一步的研究重点。 相似文献
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The classical digital speckle, or digital image, correlation method of deformation measurement is based on gray level correlation between unformed and deformed digital images. The pattern of artificial random speckles and the natural textures on some object's surfaces have fractal characteristics, and their fractal dimensions represent both gray and morph information. Furthermore, the fractal dimensions are stable feature parameters of the patterns. The digitized images of the patterns are confirmed to be also fractals. By this fact, a new method of displacement measurement is developed in the paper, based on the fractal dimensions correlation. The in-plane displacement fields of a body can be acquired. In order to verify the validity of the new method, an experiment has been designed and the results have been compared with those obtained from the classical digital image correlation method. The validity of the new method is not less than that of classical method. Further discussions about the traits and the developing vista of the method are given at the end. 相似文献
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Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform. 相似文献