Kriging

这是人脸识别，用MATLAB实现，非常好的东东哦(This is the face recognition, MATLAB, very good Eastern oh)

matlab的gui设计程序,有关<信号与系统>课程的辅助教学设计(Matlab GUI design, the relevant & lt;)

说明：  水下图像融合，图像融合，matlab语言(Underwater image fusion, image fusion, MATLAB language)

CT（computer tomography ）图像重建算法，FBP，是目前商用CT的主流重建算法(computer tomography reconstruction algrithm)

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)

最小噪声分离变换（Minimum Noise Fraction Rotation，MNF Rotation）工具用于判定图像数据内在的维数（即波段数），分离数据中的噪声，减少随后处理中的计算需求量(Minimum Noise Fraction Rotation (MNF Rotation) tool is used to determine the intrinsic dimension (i.e. band number) of image data, separate the noise in data, and reduce the computational requirements in subsequent processing.)

说明：  利用双线性插值法，来对图像进行放大或者缩小的操作(Bilinear interpolation is used to enlarge or shrink the image)

本程序对梯度-灰度共生矩阵进行求解，并对其进行归一化的处理。(Gradient of the program- to solve GLCM, and its normalization processing.)

这是我本科的毕业设计做的关于医学图像的基于形状的图像检索。预处理用小波去噪 ，特征选用不变矩。(This is my undergraduate graduation design done on the medical images based on the shape of the image retrieval. Pretreatment with wavelet denoising, feature selection invariant moment.)

本源代码是自己编写的关于图像小目标的检测（matlab版），其中包括对不同对比度、信噪比下的图像小目标进行检测。(The source code is written about the image of his small target detection (matlab edition), including the different contrast, signal-to-noise ratio of image detect small targets.)