susancorners

能够实现图像分割，对图像分类起到一定的分割效果(Image segmentation can be realized)

CT反投影重建的R-L滤波函数与S-L函数，应用对象为matlab自带shepp-logan模型图像(R-L function and S-L function applying to CT backproject reconstruction)

灰度图像的二维傅里叶变换(cv_gray_fft2)，二维傅里叶变换结果的幅值计算(cv_abs)，频谱平移(cv_gray_fft2shift)，将数值归一化到0到255区间(cv_range_0to255)是非常常用的四个功能！所以写成四个函数，方便将来调用！附运行截图~并附对应的MATLAB程序！(Dimensional Fourier transform of the grayscale image (cv_gray fft2), two-dimensional Fourier transform results to calculate the amplitude (cv_abs), spectral translation (cv_gray_fft2shift), the value normalized to range 0 to 255 (cv_range_0to255) is very common four function! so written as four function to facilitate future calls! attached run shot- along with the corresponding MATLAB program!)

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)

多目标质心的求取，matlab代码，适合图像处理初学者(Center of mass to strike multiple targets, matlab code for image processing for beginners)

区域生长算法分割脑部图像， 两个种子点，解决完整分割白质的算法(Region growing algorithm for segmentation of brain images, the two seed points, solve the integrity of white matter segmentation algorithm)

本程序为基于快速双边滤波器的边缘保持算法，算法具有平移不变性，具有线性复杂度(this is a edge-preserving denoising method using fast bilateral filter)

一种基于半监督的svm的图像分类方法。该方法通过聚类核的方法利用无标记样本局部正则化训练核的表达式。这种方法通过图像直接学习一个自适应的核。该程序仿真的是文章：Semi-supervised Remote Sensing Image Classification with Cluster Kernels。大家可以参考下。(A semi-supervised SVM is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image, and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictionsds)

综合多个特征的图像检索，包括颜色、形状和纹理等(Integrated multiple features for image retrieval, including color, shape and texture)

说明：  形态学方法区域分割，利用区域生长算法，实现区域分割(Morphological method for region segmentation and region growing algorithm for region segmentation)