WF_1D_CDP

主要思想是用meanshift算法跟踪目标，拖动矩形框选择目标模板，meanshift自动跟踪 本程序的主要缺陷体现在帧差法自动识别目标，这部分功能与上一个功能独立，可用可不用，用于自动识别目标，效果不是很好，主要体现在对图像视频的要求是 背景（目标以外的所有事物）不能动(The main idea is to use meanshift algorithm to track the target and drag a rectangle to select the target template, meanshift automatic tracking The main drawback of the program is reflected in the frame difference method automatically identifies the target, which is part of the function and one function independently, may or may not, be used to automatically identify the target, the effect is not very good, mainly reflected in the requirements of the video image is the background (target All things outside) can not move)

说明：  经典图像处理灰度图像去噪模型，以及改进模型效果不错(Classic image processing gray image denoising model, and improved model good results.)

主成分分析方法（PCA），PCA算法的理论依据是K-L变换，通过一定的性能目标来寻找线性变换W，实现对高维数据的降维。(Principal component analysis (PCA), PCA algorithm is based on the theory of KL transform, through a certain performance targets to find the linear transformation W, the realization of high-dimensional data, dimensionality reduction.)

用C语言实现最优化算法中的黄金分割法！！(optimization algorithm using c)

对一幅图像进行DCT与DFT变换，分析变换后的高低频分量系数(DCT and DFT on an image, analysis of high frequency components of the transformed coefficient)

模糊图像的去模糊处理，主要有利用hough变换估计模糊方向，利用radon变换估计模糊长度。(Blurred image deblurring process, mainly using the estimated blurring direction hough transform, radon transform using the estimated blur length.)

说明：  基于MATLAB语言，计算两幅图像峰值信噪比和均方差。(Computing Peak Signal-to-Noise Ratio and Mean Variance of Image)

说明：  使用vivado HLS工具实现的直方图均衡化(EqualizeHist with vivado HLS)

Visual C++下的小波变换，小波分解与重构，加入噪声分析，显示分解和重构图形。(Wavelets for data encode and uncode, the figures would be shown.)

内容包括高斯混合概率假设密度滤波器仿真程序，GM-PHD滤波器提供了一种PHD滤波器工程化的方法，在无数据关联的情况下进行目标跟踪。(This algorithm is extended to accommodate mildly nonlinear target dynamics using approximation strategies from the extended and unscented Kalman filters.)