The image histogram
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Normal distribution of the image histogram is a method to enhance the contrast of image .
图象直方图正态化,是增强图象对比度的一种方法。
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Normal distribution of the image histogram
图象直方图正态化
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The image histogram is divided into different regions . These weighted entropy is balance between the image exposure value and the ideal exposure value .
将图像的直方图划分成不同的区域,将这些区域的图像熵经过加权计算,得到该图像的曝光值与理想曝光值之间的差。
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For these target detection scene , the image histogram equalization and the weighted scoring system are used to reduce the undetected rate and false detection rate .
针对这些目标检测场景,采用图像直方图均衡及对检测评分体系加权来降低目标漏检率和误检率。
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This paper researched and implemented the image histogram equalization , neighborhood average method and median filtering technique based on the airspace method , and image gradient sharpening and Laplace mask sharpen .
本文具体研究并实现了图像的直方图均衡、基于空域法的邻域平均法和中值滤波的图像平滑技术,以及图像梯度锐化和拉普拉斯掩模锐化,并针对序列图片给出应用效果。
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This kind of method can achieve impressive visual quality enhancement but may generate extra artifacts . 3 、 classification method , which establish the image histogram model , then estimate and classify the mix tissue in each voxel use spatial information between voxels .
该类方法效果较好但有可能产生额外的图像伪影。三是分类的方法,先建立图像直方图模型,采用像素间的空间信息来估计每个像素中的混合组织类型并对其进行分类。
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And then makes an introduction about Gaussian Mixture Model ( GMM ) . If we regard every region of image histogram as a single Gaussian Model , the image histogram will be considered as the result of repeated addition by many Single Gaussian Models .
接着介绍了高斯混合模型,在图像直方图中将每个区域看作一个单高斯模型,那么图像直方图就是多个单高斯模型叠加的结果。
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First , according to the image histogram characteristics prominence stripes are cut , laser stripes are obtained . Second , several methods of laser stripe center extraction is designed , by comparing and analysis , gray weighted centroid algorithm and curve fitting method are fitting for extraction strip center .
根据图像直方图特性分割突起条纹,得到激光条纹光带,并且设计了几种提取激光条纹中心的方法,通过对比分析,灰度重心法和曲线拟合法适合条纹中心的提取。
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The image gray histogram of B component in the white background was used to segment the fruit from the background . The Chain Code Method was adopted to search the thinned boundary line .
利用白色背景下,图象的B分量灰度直方图进行图象与背景的分离,结合苹果表面光滑易反射的特点,用链符法搜索并细化轮廓,采用最小外接矩形法求横径、纵径;
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We can select some feature sub-image from the image by gray histogram .
其三,我们提出了特征子图的概念和一种利用灰度直方图量化分析来辅助人工选取特征子图的方法。
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Because of the image using dynamic histogram modification , the loss of secret information owing to the overflow problem is avoided .
由于对原始载体图像采用动态直方图调整,避免因溢出问题而造成秘密信息丢失。
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This approach can not only get the image salient region histogram flexibly with spatial color information , but also ensure the rotation invariant .
这种方法不仅能灵活地获取图像的显著区域使得颜色信息具有空间性,还能保证图像的旋转不变。
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For image segmentation problem , this paper adopts the image of gray histogram for fuzzy clustering to get appropriate gray value , and then using it to the threshold segmentation .
针对图像的分割问题,本文采用对图像的灰度直方图进行模糊聚类首先得到适宜的灰度值阈值,再利用其对图像进行分割。
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After processing the image , gray histogram distribution is of an increasing range , dynamic contrast ratio increases , and image-level flu obviously , clarity and good color effects .
经过处理后的图像,色彩度直方图分布范围得到扩展,动态对比度增大,图像层次感明显,清晰度高,色彩效果好。
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Interface implement the image gray value histogram transform adjust , image noise removal and other image processing functions , and can calculate and display the detection of the velocity field , provide convenience for the operator flow field know the situation and analysis .
界面中实现了图像的灰度值直方图变换调整、图像噪声的去除等图像处理功能,并可以计算和显示所检测的速度场情况,方便操作者对流场情况进行了解和分析。
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After the iris image gray histogram selected , appropriate threshold to isolate the pupil from the iris is chosen through the algorithm , and then the center of the pupil through the method of Gray-level projection geometry is located .
该算法首先通过虹膜图像的灰度直方图选取合适的阈值分离出瞳孔,然后采用几何灰度投影的方法粗定位瞳孔的中心。
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Consequently , an adaptive enhancement algorithm based on the study of infrared image histogram has been presented .
鉴于此,在研究红外图像特点的基础上,提出了一种基于直方图的自适应红外图像增强算法。
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Analyzing the content-based image retrieval on histogram , a novel image retrieval method based on the image edge information is proposed .
通过分析利用颜色直方图进行图像检索时存在的问题,提出了一种基于图像边缘空间分布特征的图像检索算法。
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The invariant moments of image histogram filtered is calculated and revised with the related coefficient of the two images .
该算法的主要思想是首先计算图像直方图不变矩,然后用两幅符号图像之间的相关系数来修正,利用修正后的不变矩来检测符号图像变化。
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To better understanding the weld image , the histogram equalization method was used aiming at enlarging the difference between groove and other area .
运用直方图均衡化方法强化坡口与非坡口的差别,增加焊缝图像的理解性。
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The content-based image retrieval on histogram was analyzed and a new spatial image descriptor for image retrieval was proposed based on the color vector angle .
在分析利用颜色直方图进行图像检索时存在问题的基础上,提出了一种新的图像空间描述符。
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The image enchancement based on histogram equalization and specification can improve the contrast details and the dynamic range of gray level of the image .
基于直方图均衡化和规定化处理的图像增强技术,能有效地改善图像的对比度和灰度动态范围。
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It transforms gray levels according to alum blossom image ′ s feature of low contrast , and then binarizes the image based on its histogram .
此方法根据矾花图像低对比度的特点,运用一致性测度变换灰度,然后基于直方图进行二值化处理。
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Then , enhancing the original image based on histogram equalizing , segmenting the enhanced image by threshold , extracting the binary edge map of the segmented image ;
然后,对用直方图均衡化方法增强了对比度的虹膜图像进行阈值分割,提取分割后的图像的二值边缘图像;
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After application the image enhancement ( with histogram equalization and grey level adjustment ) and the image smoothing ( with spatial equalization filtering , median filtering and Wiener filtering ), we find they cannot remove the noise of the background .
在利用图像增强(直方图均衡化和灰度级调整)和图像平滑(空间均值滤波、中值滤波和维纳滤波器)对图像进行分析之后,发现图像预处理并未达到预期的滤波去背景噪声的效果。
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Firstly , the paper uses the color image histogram threshold segmentation methods , which choose HSV color space and evaluate the pore segmentation effects .
首先选择HSV颜色空间,利用彩色图像直方图阈值分割方法,并对孔隙分割结果进行评价。
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Improved the quality of the original image by histogram equalization and gray level histogram specification .
通过对原始图像进行灰度直方图均衡化和灰度直方图规定化来改善原始图像的质量。
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In the new method , the image gray histogram is used to compute Fisher criterion function value of all gray grades , and the optimal threshold is determined at the maximum value of Fisher criterion function .
该方法利用图像直方图计算各灰度级下的Fisher评价函数值,其最大值即对应于最佳分割阈值。
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A detection method based on image segmentation is proposed to detect garbage hoarding . By using the difference between the background image color histogram , the clustering segmentation is used to detect the garbage hoarding region .
最后将图像分割方法应用于违章行为检测中,首先提出一种基于图像分割的垃圾囤积检测方法,其利用背景图像的彩色直方图之间的差别,通过聚类分割得到垃圾囤积区域。
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Second , Binary image is obtained by utilize the information of shadow of stone and the gray image histogram .
在获取分割图像后,利用石块底部阴影信息和原始图像的灰度直方图分布特征,将分割图像二值化。