共查询到18条相似文献,搜索用时 156 毫秒
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图像跟踪中的边缘检测技术 总被引:2,自引:0,他引:2
为提高电视图像跟踪系统的图像检测精度,实现对目标的稳定跟踪,研究一种有效、实时的图像检测方法非常必要。本文介绍了边缘检测技术的基本原理,描述了几种边缘检测方法,如传统的基于经典微分算子的边缘检测、LOG滤波器与Marr Hildreth边缘检测算子、多灰度图像边缘聚焦法、Canny边缘检测算子、基于梯度信息的自适应平滑滤波和基于小波的边缘检测算子等。给出了边缘检测技术在实际图像跟踪中的应用实例,指出实际的电视图像跟踪系统可以根据不同的图像类型,考虑安全性、稳定性、精度噪声等因素,选择最优的边缘检测方法。 相似文献
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利用平稳小波变换的多尺度边缘检测算法分别对模糊图像、低对比度图像和加入噪声的图像进行了边缘检测,验证了多尺度二次B样条小波的检测效果,也比较了三种小波局部模极大值方法在抗噪性、计算量及检测效果等方面的性能,并且针对对比度低,受噪声污染严重的目标图像,提出一种能够根据不同背景计算出自适应阈值的新方法,使其在抗噪的同时又能较好地提取出微弱目标边缘。实验证明,利用多尺度二次B样条小波边缘检测算法能有效地排除噪声干扰,准确地提取出微弱边缘,可以实现3%对比度下的有噪图像的目标探测问题。 相似文献
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提出了一种保持图像细节和高抗噪性的图像融合新方法。这种方法首先对源图像进行多尺度形态学开闭滤波,得到源图像的低频平滑图像;然后应用多尺度Top-hat变换和Bottom-hat变换来提取小于相应尺度的图像细节特征。因为在较小的尺度特征中包含噪声颗粒的可能性较大,据此修正了Top-hat变换和Bottom-hat变换的相应系数;最后对以上两步骤得到的低频平滑图像和多尺度高频细节图像分别进行图像融合,应用形态学重建过程生成融合图像。实验表明,这种融合方法具有图像细节保持完整和噪声消除效果好的优点,处理效果优于传统的图像融合方法。 相似文献
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针对微钙化点容易漏检的问题,提出一种非下采样轮廓波变换结合对比度受限自适应直方图均衡的乳腺图像微钙化点增强新算法。对乳腺图像预处理,提取乳房区域并将胸肌区域去除;再对图像进行非下采样轮廓波变换提取多尺度、多方向的子带,对其中的多个高频子带采用高斯拉普拉斯算子检测边缘并增强;进一步采用对比度受限自适应直方图均衡算法,提高图像局部小区域的对比度,实现乳腺图像微钙化点增强算法。结果表明该方法是一种有效的乳腺钼靶图像微钙化点增强方法,为微钙化点检测和乳腺癌诊断提供支持。 相似文献
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基于三次样条插值的图像多尺度方向边缘重构 总被引:1,自引:0,他引:1
为了检测小结构的轮廓以及大目标的边缘,将多尺度边缘检测与小波变换有机地结合起来,利用小波分析方法来研究信号的多尺度边缘特征。针对图像信号的多尺度边缘检测和重构问题,利用二进小波变换的多尺度分析特性,定义了图像在水平和垂直方向的多尺度边缘。同时,利用三次样条插值算法,提出了一种由二进小波变换在水平和垂直方向的极值重构图像信号的算法。实验结果显示多尺度重建方法与著名的交替投影算法相比,算法复杂度低,图像重建速度提高了20倍,而且重建图像质量较好,其峰值信噪比提高了1 dB以上。 相似文献
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多尺度形态算子融合图像滤波技术及滤波质量评价 总被引:1,自引:0,他引:1
针对舰载红外警戒系统的红外和电视图像,提出了一种新的海空背景下受强杂波、噪声污染的图像目标滤波算法和滤波效果的定量评价算子。算法采用多尺度的形态算子对输入的图像并行滤波,大尺度形态算子抑制图像噪声,小尺度形态算子提取目标边缘细节信息。处理后的图像进行基于树状小波帧变换的图像信息融合,融合图像可完备提取不同尺度滤波后的图像信息。针对目标检测跟踪的图像滤波算法的评价,提出了目标与背景的交叉分辨力评价算子及评价准则。仿真实验表明。该滤波算法要优于中值滤波、自适应滤波、小波变换滤波算法,滤波质量的定量评价算法是合理的、有效的。算法适用于舰载红外警戒系统。 相似文献
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Edge detection is an important technology in image segmentation, feature extraction and other digital image processing areas. Boundary contains a wealth of information in the image, so to extract defects’ edges in infrared images effectively enables the identification of defects’ geometric features. This paper analyzed the detection effect of classic edge detection operators, and proposed fuzzy C-means (FCM) clustering-Canny operator algorithm to achieve defects’ edges in the infrared images. Results show that the proposed algorithm has better effect than the classic edge detection operators, which can identify the defects’ geometric feature much more completely and clearly. The defects’ diameters have been calculated based on the image edge detection results. 相似文献
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In this paper, an extended version of image edge detector using Green's function approach is proposed for detection of edges in the color vector space field. In the proposed method, the relationship between the Red, Green and Blue components is considered to design a differential operator for detection of edges in color images. By using the proposed operator, partial derivatives of all components of color image can simultaneously affect on the edge detection process. Therefore the proposed method can preserve the vector nature of color images during the edge processing stages. Also, the proposed method is compared both quantitatively and qualitatively with other color edge detectors. Experimental results show that the proposed method can efficiently preserve the edges even when the color images corrupted with different levels of noise. 相似文献
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一般的边缘加权Hausdorff算法,由于单尺度边缘检测算子本身对噪音敏感,会造成真实和虚假边缘显著性差异小,从而加权后对噪音鲁棒性改善有限.为此,提出了一种基于多尺度边缘测度融合加权的Hausdorff景象匹配算法.对图像提取多尺度边缘测度后,引入证据推理理论,提出一种双向指数基本置信指派构造方法,并构造出多尺度边缘测度的基本置信指派函数,然后采用冲突再分配DSmT组合规则进行融合.为了进一步区别真实边缘与高频噪音,对加权Hausdorff公式进行了一些改进,给出了更为有效利用融和后边缘测度的加权Hausdorff公式.对可见光和SAR景象的匹配实验证明:本文算法所提取边缘在抑制噪音的同时保留了大量景象细节信息,并通过横向对比验证本文算法提高了噪音鲁棒性. 相似文献
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A method of image edge detection using the Hopfield neural network (HNN) is proposed in this paper.The image edge parameters are introduced in detail, and the energy function of HNN is given based on the edge parameters. Tests on the image edge detection show that images detected by the proposed method have good edge closeness and true edge, at the same time it has good anti-noise performance. The image edge detection using HNN is better than that obtained by some other edge detection operators. 相似文献
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Improved multi-scale wavelet in pantograph slide edge detection 总被引:1,自引:0,他引:1
The mainstream methods of pantograph slide edge detection are based on canny operator and multi-scale wavelet. The former has good single edge response but the edge is fractured, the latter performs good edge continuity but contains excessive edge points. This paper combines the advantages of both methods and proposes as an improved multi-scale wavelet edge detection method based on canny criteria. Firstly we filtered the pantograph image with edge-preserving symmetric near neighbor filter. Secondly calculated the Gaussian wavelet modulus and arguments at all levels of scale, then suppressed the non-maxima value of modulus along the corresponding arguments. At last, we integrated the modulus drawings at all levels of scale, and connected edge with applicable dual-threshold. Experiments results show that the improved algorithm has both satisfactory performances in single edge response and edge continuity, it markedly improves the efficiency of edge detection algorithm. Peak signal to noise ratio (PSNR) analysis finds that the improved algorithm exceeds canny operator and traditional multi-scale wavelet edge detection. Moreover, it has higher positioning accuracy, clearer details and better noise performance. 相似文献
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Xiangzhi Bai 《Optik》2013
To efficiently extract all the possible linear features in image, a multi-scale multi-structuring element top-hat by reconstruction operator based algorithm with simple post-processing is proposed in this paper. Multi-scale top-hat by reconstruction operator using multi-scale structuring elements is discussed, firstly. Also, through importing multi-structuring elements with linear shapes at different directions, multi-scale multi-structuring element top-hat by reconstruction operator for linear feature extraction is shown. By using the multi-scales of multi-structuring elements, the method of extracting all the possible linear feature regions in an image is proposed. After extracting the linear feature regions, the final detected linear features, which are expressed as lines with different shapes and lengths, are obtained through image binarisation and refinement. Experimental results on different types of images show that, the proposed algorithm is efficient for linear feature detection and could be widely used in different applications related to multiple linear feature detection. 相似文献