共查询到16条相似文献,搜索用时 843 毫秒
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在机器人路径规划中,机器人数字路标识别是很重要的,图像的预处理会影响识别结果。图像增强技术是提高预处理结果的一种有效方法,模糊图像增强算法是目前广泛使用的一种增强算法。针对Pal模糊图像增强算法在隶属函数的定义和渡越点选择上的缺点,提出了一种改进的模糊增强算法。本算法首先使用OTSU算子自动选择最佳阈值,解决渡越点需要人工设置的缺点,并消除选择的随机性。然后修改模糊增强算法的核心隶属函数式,解决了图像像素的低灰度值被硬性设置为0的缺陷,从而改善了图像信息损失的问题。最后,将改进的算法用于处理Pioneer Ⅲ机器人的数字路标图像。实验结果表明,与现有的模糊增强算法相比,提出的算法可以取得好的效果,且提高了运算速度,具有一定得实用性和推广性。 相似文献
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二维广义模糊熵图像阈值分割法 总被引:1,自引:1,他引:0
针对一维广义模糊熵不能有效处理含噪图像的分割问题,在二维灰度直方图上定义了图像的二维隶属度函数,提出了二维广义模糊熵阈值分割法.该方法不仅考虑了图像的点灰度值,同时考虑了图像像素的邻域平均灰度值,能更好地利用图像中的信息.为了提高二维广义模糊熵阈值法的运行速度、解决参量选取问题,结合粒子群优化搜索方法,设计了嵌套式的优化过程.实验表明,二维广义模糊熵阈值分割法对噪音图像有更好的适应性. 相似文献
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二维广义模糊熵图像阈值分割法 总被引:4,自引:3,他引:1
针对一维广义模糊熵不能有效处理含噪图像的分割问题,在二维灰度直方图上定义了图像的二维隶属度函数,提出了二维广义模糊熵阈值分割法.该方法不仅考虑了图像的点灰度值,同时考虑了图像像素的邻域平均灰度值,能更好地利用图像中的信息.为了提高二维广义模糊熵阈值法的运行速度、解决参量选取问题,结合粒子群优化搜索方法,设计了嵌套式的优化过程.实验表明,二维广义模糊熵阈值分割法对噪音图像有更好的适应性. 相似文献
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X射线数字纹理图像的特征提取 总被引:1,自引:1,他引:0
以减少图像背景和结构纹理对特征提取的干扰为目的,提出了先去除背景和纹理,再进行特征分析的算法.该算法通过最小二乘法则拟合了类抛物线曲面函数提取数字射线图像的背景,减少了背景对图像特征的模糊,在此基础上,针对图像的结构纹理特点确定几何分布参量,定义减法运算公式消隐图像纹理,减少了纹理造成的图像灰度起伏,图像灰度级分布均匀.在平坦的图像背景中,根据数字射线图像信号点服从正态分布规律特点,设定阈值进行特征分割. 相似文献
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基于模糊集的自适应红外图像边缘锐化算法 总被引:2,自引:0,他引:2
针对红外图像边缘模糊和非均匀性噪音强的特点,提出了一种基于模糊集的自适应红外图像边缘锐化方法.针对图像边缘细节和噪音难以表示和区分的特点,分别建立噪音、弱边缘和强边缘的模糊特征隶属度函数,并且提取图像信息自适应调整隶属度函数;通过隶属度函数将图像映射到模糊特征平面,由模糊特征平面控制图像边缘锐化系数.该方法不仅能够锐化红外图像边缘,而且改善了传统边缘锐化算法对图像噪音放大的缺点,避免了对强边缘的过渡增强导致图像出现过增强现象,改善了图像质量. 相似文献
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True estimation of the boundary of a road crack and its size is a major task for its automatic detection. The improvement of visual effects of a road image is necessary for such a task. Therefore, we propose an automatic ridgelet image enhancement algorithm. A nonlinear function plays an important role in the enhancement algorithm in the ridgelet domain of an image. However, it is difficult to adjust the parameters of the nonlinear function adaptively with the variation of the road crack image input. Based on the fuzzy entropy criterion, we introduce two fuzzy divergences and two supplementary linear combinations between the fuzzy entropy and two fuzzy divergences as new measurements to solve the threshold segmentation problem in the ridgelet domain. According to the distribution histogram of magnitudes of the ridgelet high-frequency coefficients, we obtain the optimal segmentation thresholds that act as the parameters of the nonlinear function by using the maximum or minimum measurements of fuzzy entropy and fuzzy divergence, respectively. The self-adaptive nonlinear function makes it possible to realize the automatic enhancement of a road crack image. Experimental results show that our image enhancement algorithm can effectively enhance the global and local contrastive effects on road crack images. 相似文献
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In this paper, a target extraction method in forward-looking infrared (FLIR) images based on fuzzy thresholding which used
local characteristics, bi-modality and adjacency, is proposed. The bi-modality represents how a pixel is classified into a
part of a target using distribution of pixel values in a local region, and the adjacency is a measure to represent how far
each pixel is from the target region. Segmentation is processed by the following: First, membership values for each pixel
are calculated using bi-modality and adjacency. Second, fuzzy thresholding is performed to extract the target from the background.
Finally, we extract the precise target in the thresholded image by post-processing. To evaluate the performance of the proposed
target extraction method, we compare the proposed method with other segmentation methods using various FLIR images. Experimental
results show that the proposed algorithm has good segmentation performance. 相似文献
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A novel morphological filtering algorithm is proposed for suppressing speckle noise in images. The algorithm employs directional morphological close-open and open-close operations, then computing the membership of the filtered versions' every pixel according to the designed fuzzy rule. The final filtered image is composed of all the pixels with corresponding maximal membership. The validity of the algorithm is demonstrated. 相似文献
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Infrared polarization and intensity imagery provide complementary and discriminative information in image understanding and interpretation. In this paper, a novel fusion method is proposed by effectively merging the information with various combination rules. It makes use of both low-frequency and high-frequency images components from support value transform (SVT), and applies fuzzy logic in the combination process. Images (both infrared polarization and intensity images) to be fused are firstly decomposed into low-frequency component images and support value image sequences by the SVT. Then the low-frequency component images are combined using a fuzzy combination rule blending three sub-combination methods of (1) region feature maximum, (2) region feature weighting average, and (3) pixel value maximum; and the support value image sequences are merged using a fuzzy combination rule fusing two sub-combination methods of (1) pixel energy maximum and (2) region feature weighting. With the variables of two newly defined features, i.e. the low-frequency difference feature for low-frequency component images and the support-value difference feature for support value image sequences, trapezoidal membership functions are proposed and developed in tuning the fuzzy fusion process. Finally the fused image is obtained by inverse SVT operations. Experimental results of visual inspection and quantitative evaluation both indicate the superiority of the proposed method to its counterparts in image fusion of infrared polarization and intensity images. 相似文献
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A new contrast enhancement algorithm for image is proposed employing wavelet neural network (WNN)and stationary wavelet transform (SWT). Incomplete Beta transform (IBT) is used to enhance the global contrast for image. In order to avoid the expensive time for traditional contrast enhancement algorithms,which search optimal gray transform parameters in the whole gray transform parameter space, a new criterion is proposed with gray level histogram. Contrast type for original image is determined employing the new criterion. Gray transform parameter space is given respectively according to different contrast types,which shrinks the parameter space greatly. Nonlinear transform parameters are searched by simulated annealing algorithm (SA) so as to obtain optimal gray transform parameters. Thus the searching direction and selection of initial values of simulated annealing is guided by the new parameter space. In order to calculate IBT in the whole image, a kind of WNN is proposed to approximate the IBT. Having enhanced the global contrast to input image, discrete SWT is done to the image which has been processed by previous global enhancement method, local contrast enhancement is implemented by a kind of nonlinear operator in the high frequency sub-band images of each decomposition level respectively. Experimental results show that the new algorithm is able to adaptively enhance the global contrast for the original image while it also extrudes the detail of the targets in the original image well. The computation complexity for the new algorithm is O(MN) log(MN), where M and N are width and height of the original image, respectively. 相似文献