椭圆拟合

图像处理中比较有用的二维图像光谱分析，Matlab源代码(Image processing more useful two-dimensional image spectra, Matlab source code)

包涵了计算影像的几种质量指标，这些指标都是全局指标，对影像质量评价有一定作用(Image Quality Index ：IFC、Q4、QNR、VIF)

opencv函数包，用于matlab调用(opencv function package, calls for matlab)

说明：  用于MATLAB的支持向量机的工具箱，用于训练与验证(Support vector machine (SVM) for MATLAB toolbox, used for training and validation)

FCM和稀疏场水平集用于分割医学图像分割(FCM and sparse field level set for segmentation of medical image segmentation)

实现了立体匹配的SAD算法计算视差图，结果比较理想(Using the SAD algorithm to calculate the disparity map of stereo matching, the result is good.)

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)

为图像添加各种噪声，如高斯噪声、泊松噪声、椒盐噪声等。（需有openCV）(Add all kinds of noise for the image, such as Gaussian noise, Poisson noise, salt and pepper noise. (The need for openCV))

PSNR图象质量评价模型，PSNR图象质量评价模型方法(Image quality evaluation model PSNR, PSNR method of image quality evaluation model)

形态学pathopenings的实现，对线特征提取等图像处理有令人惊奇的效果。(Morphological pathopenings the realization of the line feature extraction and other image processing have surprising effects.)