fcmimage

说明：  用于三维空间坐标系变换的7参数模型，在设计坐标系变换的各行业应用中用的最多，从数学角度来说也是最严密的转换方法。 由于结果中最多可求得七个转换参数，即三个平移参数、三个旋转参数(Ex、Ey、Ez)和一个尺度缩放因子(m)，因此，通常也被称为七参数法。 (Three-dimensional coordinate system transformation for the 7 parameter model, coordinate system transformation in the design of applications using the most, the industry, from the mathematical point of view, the conversion is the most rigorous methods. Since the results can be obtained up to seven transformation parameters, ie three translation parameters, three rotation parameters (Ex, Ey, Ez) and a zoom scale factor (m), therefore, often referred to as seven-parameter method.)

全套的DCT域数字水印源代码matlab(A full set of digital watermarking of DCT-domain source code matlab)

对于读入的彩色图像在rgb和hsv域中进行均衡，并显示比较均衡效果(To read the color image in rgb and hsv domain balanced and shows the effect of a more balanced)

1、对观测数据进行中心化，； 2、使它的均值为0，对数据进行白化—>Z； 3、选择需要估计的分量的个数m，设置迭代次数p<-1 4、选择一个初始权矢量（随机的W，使其维数为Z的行向量个数）； 5、利用迭代W(i,p)=mean(z(i,:).*(tanh((temp) *z)))-(mean(1-(tanh((temp)) *z).^2)).*temp(i,1)来学习W （这个公式是用来逼近负熵的） 6、用对称正交法处理下W 7、归一化W(:,p)=W(:,p)/norm(W(:,p)) 8、若W不收敛，返回第5步 9、令p=p+1，若p小于等于m,返回第4步 剩下的应该都能看懂了 基本就是基于负熵最大的快速独立分量分析算法(1, on the center of the observation data, 2, making a mean of 0, the data to whitening-> Z 3, select the number of components to be estimated m, setting the number of iterations p < -1 4, select an initial weight vector (random W, so that the Z dimension of the row vectors of numbers) 5, the use of iteration W (i, p) = mean (z (i, :).* (tanh ((temp) ' * z)))- (mean (1- (tanh ((temp)) ' * z). ^ 2)).* temp (i, 1) to learn W (This formula is used to approximate the negative entropy) 6 with symmetric orthogonal treatments W 7, normalized W (:, p) = W (:, p)/norm (W (:, p)) 8, if W does not converge, return to step 5 9 , so that p = p+1, if p less than or equal m, return to step 4 should be able to read the rest of the basic is based on negative entropy of the largest fast independent component analysis algorithm)

说明：  下拉框自动提示 输入内容可直接显示出所匹配的所有信息(Drop-down box automatically prompt input all the information can be displayed directly matched)

DPC算法的经典实现过程，包含元数据集、决策图以及2维条线下密度聚类(The classical implementation process of DPC algorithm includes metadata set, decision diagram and 2 dimensional lower density clustering)

高通高斯滤波，LBP，LDP的matlab源代码，用于图像的增强，特征提取。(High-pass Gaussian filter, LBP, LDP matlab source code for image enhancement, feature extraction.)

生成SAR图像程序，可以生成幅度SAR图像和强度SAR图像。(This procedure generate SAR images, and it can generate the amplitude SAR image and the intensity SAR image .)

Gabor滤波器的实现函数，与一般网上下载的不同，滤波效果更好，易于提取图像特征(Gabor filter implementation function, and general downloading different, better filtering, easy to extract image features)

案例推理,用于匹配,欢迎大家交流,有资源共享,(Case-based reasoning for matching, welcomed the U.S. exchange, resources sharing,)