experiment

视频修复的效果非常的好，而且速度还挺快的，挺好用的，可以试试(video inpainting)

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)

利用matlab提取掌纹图像的感兴趣区域，ROI提取(Extract palmprint images using matlab region of interest, ROI extraction)

对比两张图片上的散斑的变化来确定被测材料的变形和相关位移(Change of speckle contrast two images to determine the detected material deformation and displacement)

这是对6—PUS并联机器人的运动学仿真及运动轨迹跟踪(This is the kinematics simulation and trajectory tracking of the 6-PUS parallel manipulato)

susan角点检测的源代码。简单易学附带中文程序说明(susan corner detection of the source code. Relatively simple description of the procedures with the Chinese)

基于小波变换的人脸识别代码本代码对图像进行小波分解，然后又用最近邻方法实现了图像的识别。(Face Recognition Based on Wavelet Transform code-wavelet based face recognition, the code of the image wavelet decomposition, and then with the nearest neighbor method to achieve the image recognition!)

实现图像的Contourlet变换，显示图像变换后每一层的图像。(Realize the Contourlet transform of the image , each layer of image is displayed after transform.)

水平集图像分割代码，对应论文为Li C, Xu C, Gui C, et al. Level set evolution without re-initialization: a new variational formulation[C]//Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on. IEEE, 2005, 1: 430-436.(Level set image segmentation code, the corresponding papers of Li C, Xu C, Gui C, et al Level set evolution without re-initialization:.. A new variational formulation [C]// Computer Vision and Pattern Recognition, 2005 CVPR 2005 IEEE. Computer Society Conference on IEEE, 2005, 1:. 430-436.)

相移三步法、四步法、五步法及相应的相位解包裹程序(?àò?èy 2?·¨? ￠ ?? 2?·¨? ￠ ?? 2?·¨?° ?àó | μ??à? ?? a ° ü 1 ü 3 ìDò)