中心线提取

RPCA (Robust Principal Component Analysis)是目前用于矩阵填充、图像去噪的最有效的优化方法。目前最有效的算法是ALM（Augmented Lagrange Multiplier）。ALM分为Exact ALM和Inexact ALM。 该代码是Inexact ALM，收敛速度比Exact ALM快！(RPCA (Robust Principal Component Analysis) is used for matrix filling, image denoising. It is currently the most effective optimization method. Currently the most effective method is ALM (Augmented Lagrange Multiplier). There re 2 kinds of ALM: Exact ALM and Inexact ALM. The code is Inexact ALM, faster convergence speed than the Exact ALM!)

图像纹理特征提取matlab，计算图像的粗糙度、方向度等特征。(Image texture feature extraction matlab, calculated image roughness, and other characteristics of the direction of degrees.)

说明：  运用低通滤波器，中心削波和自相关技术估计一段男性和女性语音信号的基音周期，画出基音轨迹曲线，给出估计准确率。(The use of low-pass filter, the center clipping and related technologies is estimated from a male and female speech signal pitch period, pitch trajectory drawn curves of estimated accuracy.)

This file contains functions to solve volume of fluid function to track free surface.

说明：  迭代收缩阈值算法和快速收缩阈值迭代算法求解Lasso问题(Iterative Shrinkage Thresholding Algorithm (ISTA) for LASSO problem)

基于ASEF方法的人眼精确定位方法,解压后，在目录中有一个使用说明文件，可以帮助你使用它(Method based ASEF precise eye positioning method, unpacked, in the directory has a file using the instructions that can help you use it)

填充区域图像，设置填充区域，填出图像的颜色(Filled regional images, set fill area, fill in the color of the image)

用代数迭代算法ART重建图像，含MATLAB代码(image reconstruction using ART algorithms (MATLAB code))

Zhang等人 利用相位一致性信息的特性，提出了 特征相似性方法(FSIMG) ，选取了相位一致性信息和梯度信息 作为它的两个特征，得到了较好的结果。 (A novel feature similarity (FSIM) index for full reference IQA is proposed based on the fact that human visual system (HVS) understands an image mainly according to its low-level features. Specifically, the phase congruency (PC), which is a dimensionless measure of the significance of a local structure, is used as the primary feature in FSIM. Considering that PC is contrast invariant while the contrast information does affect HVS’ perception of image quality, the image gradient magnitude (GM) is employed as the secondary feature in FSIM. PC and GM play complementary roles in characterizing the image local quality. After obtaining the local quality map, we use PC again as a weighting function to derive a single quality score. Extensive experiments performed on six benchmark IQA s demonstrate that FSIM can achieve much higher consistency with the subjective uations than state-of-the-art IQA metrics.)

卡尔曼滤波的一个典型实例是从一组有限的，包含噪声的，对物体位置的观察序列（可能有偏差）预测出物体的位置的坐标及速度。在很多工程应用(如雷达、计算机视觉)中都可以找到它的身影。同时，卡尔曼滤波也是控制理论以及控制系统工程中的一个重要课题。(A typical example of the Kalman filter, from a limited set, containing the noise, the position of the object observed sequence (there may be deviation) to predict the coordinates of the location and speed of the object. Its presence can be found in many engineering applications (such as radar, computer vision). Meanwhile, the Kalman filter is control theory, and control is an important topic in systems engineering.)