bfilter.tar

说明：  用matlab编写的基于轮廓最大互信息图像配准算法(Prepared using matlab contour based on the maximum mutual information image registration algorithm)

张正友相机标定源码，数据及图片，包含说有文件，能正常运行(zhang s calibration)

有关数字图像退化函数的估计与滤波，维纳滤波器实现，运动模糊等(For digital image degradation function estimation and filtering, Wiener filter implementation, motion blur, etc.)

基于压缩感知理论的目标跟踪算法，实现对可视目标的稳健跟踪(Target tracking algorithm based on compressed sensing theory)

sift图像匹配的纯matlab代码,研究图像配准的可以用这个，配准图像效果较好！！(sift pure image matching matlab code of image registration can use this, the image registration is better! !)

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)

之前下载了winform实现Echart统计图（基于webBrowser）有了echart在winform的应用。但发现他实际上是静态页面的，统计图未有数据交互功能。本例主要通过C#winform给echart赋值，实现数据动态交互。 

基于压缩感知的图像加密算法，稀疏基用的是小波，重构用的是OMP(Compressed sensing image encryption algorithm)

说明：  功能简单的截图，可以像qq那样截图，并有图片处理功能(Simple screenshots, like QQ screenshots, and image processing capabilities)

介绍了不同非线性模型在随机共振中的应用，像饱和非线性，阈值非线性等(Describes the different nonlinear model of stochastic resonance in the application, such as nonlinear saturation threshold nonlinearity. . . .)