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计算关联维的 Matlab 程序 - (mex 函数，超快)
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文件夹说明：
1、CorrelationDimension_main.m - 程序主文件
2、LorenzData.dll - 产生Lorenz离散数据
3、normalize_1.m - 数据归一化
4、PhaSpaRecon.m - 相空间重构
5、CorrelationDimension.dll - 计算关联积分函数
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用于灰色关联系数和灰色关联度的计算，其中进行了初值化和归一化处理。,Correlation coefficient for the gray and gray correlation calculation, which carried out the initial value of and normalized.
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归一化互相关高速计算模块OpenCV工程,Daniel Eaton已将其生成Matlat Mex文件,比Matlab内建的normxcorr2()效率要高-Normalized cross-correlation of high-speed calculation module, Daniel Eaton have been wrapped the C++ code from OpenCV project and making it available as a MATLAB MEX-file,
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matlab 图像处理 显示两幅子图像的归一化互相关-matlab image processing show that two sub-image of normalized cross-correlation
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The normalized cross correlation (NCC) implemented in C++ and Matlab
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ZNCC Normalized cross correlation
m = zncc(w1, w2)
Compute the zero-mean normalized cross-correlation between the two
equally sized image patches w1 and w2. Result is in the range -1 to 1, with
1 indicating identical pixel patterns.-ZN
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matlab 归一化相关系数，可用于模板匹配-matlab normalized correlation coefficient
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MATLAB语言的归一化相关匹配算法Normalized correlation algorithm-MATLAB language Normalized Correlation Matching Algorithm Normalized correlation algorithm
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归一算法用在灰色关联度的计算，可以计算出权重，然后进行关联度计算。-Normalized correlation algorithm is used in the calculation of the gray, you can calculate the weights and then calculated correlation.
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Matlab and c code to compute fast normalized correlation coefficient.
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归一化相关算法
归一化
图形图像处理-Normalized correlation algorithm normalized Graphics and Image Processing
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本程序展示了二维归一化互相关用于
模式匹配和目标跟踪。该程序提示用户选择感兴趣的（ROI）的区域和对同类目标进行跟踪的数目。归一化交叉相关图表明，当值已超过设定的阈值时目标就已经确定。-This demo illustrates the use of 2-D normalized cross-correlation for
pattern matching and target tracking. The demo prompts the user to select
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实现了三种图像匹配算法
1：归一化互相关匹配算法
2：基于Hausdorff距离的图像匹配算法
3：图像不变矩匹配算法-Three matching algorithms to achieve 1: normalized cross correlation matching algorithm 2: the image matching algorithm based on Hausdorff Distance 3: Image Invariant Moment Matchin
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基于小波变换的多分辨匹配算法:
首先利用小波的多分辩率特性将匹配图像和模板图像分解到乙层上，并且只保留LL低频部分，然后利用归一化相关法作为相似性度量，进行由粗到细的相关匹配过程，每次利用下一层的匹配结果在上层小范围内搜索。这样做极大地减少了搜索空间，而且减少了每次匹配计算相似度的数据量。
-Wavelet multiresolution matching algorithms: a wavelet multi-resolution feature will match the imag
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基于灰度的归一化匹配算法：将原图以及匹配图灰度化，算出相关系数后得到匹配区域。-Based on Gray' s normalized matching algorithms: the original image and the gray level of matching graph, calculate the correlation coefficient obtained after the matching area.
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图像配准：选择图像需要配准的子区域，计算归一化互相关，通过它来确定图像配准的区域，显示配准后的图像。-Image registration: Select the image sub-region need registration, computing normalized cross-correlation, by which to determine the image registration area to show the image after registration.
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快速NCC(normalized cross correlation)算法实现。比matlab自带的normxcorr2 快10-20倍。在windows Unix环境下c语言，和matlab编译通过。-use Matlab on Windows or Linux or Mac OS X and want fast (exact, general-case) normalized correlation (NCC) code right now, then download it and enj
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图形图像的峰值信噪比和归一化相关系数matlab编程源代码-Graphic image of the peak signal to noise ratio and normalized correlation coefficient of matlab programming source code
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matlab codes to determine normalized correlation, psnr and log of an image
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实现归一化相关系数NC的计算，测试有效，需自己替换两张所需计算的图片(The calculation of normalized correlation coefficient NC is effective, and we need to replace two pictures that we need to calculate.)
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