duibiduzengqiang

/** * jpg图像文件缩放类 * * 本类实现一个对 JPG/JPEG 图像文件进行缩放处理的方法 即给定一个 JPG 文件，可以生成一个该 JPG 文件的缩影图像文件 (JPG 格式 ) *，(/ * * * JPG * * the zoom image file class to implement a class of JPG/JPEG image file to zoom method is given a JPG file, you can generate a miniature image file of the JPG file (JPG format) *,)

图像处理的偏微分方程方法，包括曲线演化，图像分割，图像滤波，图像复原等的matlab源代码。(Partial differential equations of image processing methods, including curve evolution, image segmentation, image filtering, image restoration, etc. matlab source code.)

说明：  利用区域能量方法的matlab图像处理程序直接可用(Use of regional energy method matlab image processing program can be used directly)

rcmc: 距离徙动算法.SAR多点目标成像算法。含主瓣宽度和积分旁瓣比的求解。(rcmc: range migration algorithm. SAR multi-point target imaging algorithms. Including the main lobe width and sidelobe ratio integral solving.)

基于规格化Hough变换的天波超视距雷达检测前跟踪算法(Hough transform based on the normalized horizon radar detection and tracking algorithms)

经典的K均值聚类，源码加利用三维高斯简单数据的实现对三类数据的聚类(Achieve the effect of classical K-means clustering, plus simple data)

sift角点检测及匹配，在不同尺度空间下的角点检测方法，很方便实用。(sift corner detection and matching, the corner detection methods under different scales of space, it is convenient and practical.)

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：  当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。( This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio)

说明：  进行图像的特征提取，为图像拼接做准备，matlab(Feature extraction of image)