mtf

对于图像进行ANORLD变换，在图像嵌入水印的过程中，可以对要嵌入的水印图像先进性置乱操作，可以有效地抵抗剪切攻击(For images ANORLD transform, watermark embedding in the image of the process, can the watermark image to embed the advanced nature of the scrambling operation, can effectively attack the shear resistance)

点云的配准实验s-icp算法 实现两个点云数据的对准(A scale stretch method based on ICP for 3D data registration)

大恒相机二次开发，单次采集

Relief-F 算法是由 Kononenko 在 Relief 算法基础上扩展得到的，可以用来解决多分类与回归问题。 Relief-F 特征选择算法利用特征与类别间的相关程度判别特征的敏感程度，敏感的特征能使同类样本靠近，非同类样本远离。基本思想是： 先随机从总样本集 D中获取一个样本 R， 然后在 与 R 同类样本集中和与R 异类 样 本 集 中 各 获 取 k 个近 邻 样 本， 在 特 征 集 F中如果某个特征上异类样本的距离大于同类样本，则这个特征是有利于分类的，增加其权重，重复 n 次 取所有结果的均值作为每个特征的最终权重值.

结合图像处理MATLAB的基本原理和知识，详细介绍了手指静脉预处理，图像分割，静脉纹路分割，滤波去噪，细化等相关内容。(Combined with the basic principle and knowledge of image processing, this paper introduces the finger vein pretreatment, image segmentation, vein vein segmentation, filtering and denoising, thinning and other related contents in detail.)

基本实现光流法，可以显示出两张图片中，光流的方向。(The basic realization of optical flow method, can show two pictures of the direction of flow.)

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：  Kylberg Sintorn数据集可用于进行算法的旋转不变测试，然而官网中并没有直接划分训练集与测试集，本代码对该数据集的图片进行重新命名与划分，可用于算法测试中(The Kylberg Sintorn dataset can be used to perform the rotation-invariant test of the algorithm. However, the official website does not directly divide the training set and the test set. This code renames and divides the picture of the dataset, which can be used in algorithm testing)

带有完全匹配曾的声波方程正演，从2阶精度到8阶精度可选(Had the acoustic wave equation forward with an exact match, optional 2 order accuracy to 8 order accuracy)

该源代码是采用gui界面的多种图像融合算法的集合，融合后会产生清楚的图像,并比较融合质量(Gui interface using a variety of collection of image fusion algorithm)