共查询到18条相似文献,搜索用时 140 毫秒
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基于标准差梯度的模糊边缘检测算法 总被引:2,自引:0,他引:2
红外图像的边缘检测是图像处理领域的难题之一。结合红外图像的特点,将最小误差原理推广到模糊域进而应用到红外图像的边缘检测上,提出了一种基于标准差梯度的红外图像模糊边缘检测算法。首先提出了一种基于标准差的梯度算子,将图像中潜在的边缘区域很好地区分出来;而后引入模糊最小误差阈值算法.根据此算法自适应提取了标准差梯度图像中的最优阈值,从而实现了红外图像的目标边缘检测。与传统的基于梯度的红外图像边缘检测算法进行对比实验,结果表明,该算法用于红外图像边缘检测能获得更好的效果。 相似文献
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讨论了模糊理论在边缘提取中的应用,并给出了一种改进的基于模糊理论的图像边缘检测算法。实验结果表明,与该算法不需要加额外的滤波器或图像降噪预处理。在抗噪性能方面(80%以内的Gaussian噪声和10%以内的椒盐噪声Salt&Pepper)明显优于其它方法。 相似文献
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基于小波变换的合成孔径雷达(SAR)图像斑噪声抑制算法,能很好的减小相干斑噪声对SAR图像的影响.但该算法在平滑噪声的同时,往往也会使图像的边缘变得模糊,降低了SAR图像的分辨率.比例边缘检测算法能较完整和准确的检测出SAR图像的边缘.我们试图提出一种改进算法,结合小波方法和比例边缘检测两种算法的优点.利用比例边缘检测提取出SAR图像的边缘图,用小波的方法对去边缘的图像进行去斑噪声处理,再把边缘图叠加到去噪后的图像上.试验证明这种算法能够在去除SAR斑噪声的同时,较好的保持SAR图像边缘. 相似文献
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针对印制电路板(printed circuit board, PCB)光电图像模糊且含噪声的具体情况,提出了改进的边缘信息提取算法。首先分别对自适应模糊集增强算法与数学形态学边缘检测算法(edge detection algorithm of mathematical morphology, EDAMM)实施改进,并分析了其基本原理。然后结合这两种算法对PCB光电图像进行预处理及边缘信息提取。最后对两幅由不同成像系统获取的PCB光电图像进行了边缘信息提取实验。结果表明:用本文算法获得的PCB光电图像明暗对比度较高,并提取了精确且清晰的图像边缘信息,明显减少了噪声,所得图像的优质系数较高,两幅图像的优质系数分别是0.885 2、0.874 9,均高于本文中所提到的另外4种算法的结果。可见,采用本文算法可以更好地去除PCB光电图像中的模糊与噪声,并精确地提取出PCB光电图像的边缘信息。 相似文献
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基于Canny算子的边缘提取改善方法 总被引:23,自引:1,他引:22
通过对Canny算法进行改进,提出一种对原图像开窗统计后再进行局部灰度变换的方法.该算法改善了Canny算法对灰度分布不均匀的图像进行边缘检测的效果,并与传统Canny算法进行了比较,试验结果证明了该算法能有效改善灰度分布不均匀图像的边缘检测效果. 相似文献
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Edge detection in ultrasound imagery using the instantaneous coefficient of variation 总被引:8,自引:0,他引:8
The instantaneous coefficient of variation (ICOV) edge detector, based on normalized gradient and Laplacian operators, has been proposed for edge detection in ultrasound images. In this paper, the edge detection and localization performance of the ICOV-squared (ICOVS) detector are examined. First, a simplified version of the ICOVS detector, the normalized gradient magnitude squared, is scrutinized in order to reveal the statistical performance of edge detection and localization in speckled ultrasound imagery. Both the probability of detection and the probability of false alarm are evaluated for the detector. Edge localization is characterized by the position of the peak and the 3-dB width of the detector response. Then, the speckle-edge response of the ICOVS as applied to a realistic edge model is studied. Through theoretical analysis, we reveal the compensatory effects of the normalized Laplacian operator in the ICOV edge detector for edge-localization error. An ICOV-based edge-detection algorithm is implemented in which the ICOV detector is embedded in a diffusion coefficient in an anisotropic diffusion process. Experiments with real ultrasound images have shown that the proposed algorithm is effective in extracting edges in the presence of speckle. Quantitatively, the ICOVS provides a lower localization error, and qualitatively, a dramatic improvement in edge-detection performance over an existing edge-detection method for speckled imagery. 相似文献
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Liu Xinchun Chen Shidong Zou Mouyan Chai Zhenming 《电子科学学刊(英文版)》2000,17(4):338-344
This paper presents a new method for detection of edges in digital angiographic images. It is found that variances of local regions across edges of images are statistically different from that of those where no edge is crossed. This difference can be utilized for the detection of edges of angiographic images. An algorithm based on local variance is proposed. As a result, the edge-detection algorithm is not sensitive to noise and low-level textures of images. A computer program based on the new algorithm has been developed and used by several hospitals. 相似文献
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针对传统边缘检测算法边缘信息保留不完整与边缘点定位不精确的问题,提出了一种基于二次曲面拟合的子像素边缘检测算法。利用拟合法求得子像素图,其抗干扰性强,检测位置较准确,并在此基础上利用改进的Canny算子精确地判断图像边缘位置。实验结果表明,该算法不仅提高了图像的边缘信息保留能力,且图像边缘光滑,边缘点定位精确,细节信息完全。 相似文献
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针对模糊C均值聚类算法对大数据量的情况进行分割时存在耗时过长的问题,提出基于改进四叉树的FCM分割方法。该算法首先求取图像的四叉树,将四叉树节点集合作为模糊聚类算法的样本集,减小样本空间,然后利用FCM算法实现图像的边缘分割;针对分割处理后的图像带来的锯齿状边缘,再利用曲线拟合算法对图像边缘进行平滑处理。在标准摄影师图像和肝脏核磁图像的数据集上实验,实验结果可以看出算法提高了FCM的运算速度,对医学图像具有更高的分割精度,便于为后续诊断和数据分析提供基础。 相似文献
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本文通过对边缘点的定义,提出了一种微分极值的边缘检测算法.与经典微分算法相比,该算法直接在边缘检测窗口内提取边界像素点,因此边缘定位准确,连续性好,在背景图像照度不均匀的情况下,仍能够得到令人满意的检测效果. 相似文献
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Edge detection applied to satellite imagery of the oceans 总被引:1,自引:0,他引:1
A computer edge-detection algorithm for automatic delineation of mesoscale structure in digital satellite IR (infrared) images of the ocean is developed. The popular derivative-based edge operators are shown to be too sensitive to edge fine-structure and to weak gradients to be useful in this application. The edge-detection algorithm is based on the gray level cooccurrence matrix (GLC), which is commonly used in image texture analysis. The cluster shade texture measure derived from the GLC matrix is found to be an excellent edge detector that exhibits the characteristic of fine-structure rejection while retaining edge sharpness. This characteristic is highly desirable for analyzing oceanographic satellite images 相似文献