点云特征提取 详细 实用 经典的讲述过程及方法FeatureExtractionFromPointClouds

实现图像精确分割，基于ALpha Matting 的基础上的Sharedmatting图像分割算法(Accurate image segmentation,Sharedmatting image segmentation algorithm based on ALpha Matting)

数字图像处理 小波处理 ，去噪音，比基于傅里叶变换的去噪方法好。 含噪信号经过预处理，然后利用小波变换把信号分解到各尺度中，在每一尺度下把属于噪声的小波系数去掉，保留并增强属于信号的小波系数，最后再经过小波逆变换恢复检测信号。(The noisy signal is pre-processed, then the signal is decomposed into different scales by wavelet transform. The wavelet coefficients belonging to noise are removed at each scale, and the wavelet coefficients belonging to the signal are retained and enhanced. Finally, the detected signal is restored by inverse wavelet transform. It is better than the denoising method based on Fourier transform.)

考虑雨衰 阴影 和多径影响，可以广泛的应用于数据预测及数据分析,采用了小波去噪的思想。( Consider shadow rain attenuation and multipath effects Can be widely used in data analysis and forecast data, Using wavelet denoising thought.)

在linux系统中通过卷积神经网络实现图像风格迁移(Image style migration through convolution neural network in linux)

提出一种新的基于分支结构特征的视网膜图像配准方法，此算法可降低误匹配的点。能够应用到其他图像配准中，形成良好的等级结构。(Feature-Based Retinal ImageRegistration Using Bifurcation Structures)

主要包括3种去噪方法，Bayesian Least Squares，BM3d 和Non-local means (this attachment contains three classical denoising methods Bayesian Least Squares，BM3d and Non-local means )

图像自适应阈值分割，基于直方图的图像阈值分割(Image adaptive threshold segmentation)

说明：  颗粒粗化源码，将马赛克现象认为的作用于一副图像，称之为颗粒粗化。可以用来建立图像切换效果(source of coarse particles, that the phenomenon will mosaics in the role of an image, known as particle coarsening. Images can be used for switching effects)

可以采用形态学方法找出边界，比较有益的初学者的学习方法。(It s very good for a newer to learning about image processing.)

说明：  可实现正割法求解，牛顿法，迭代法，抛物线求根(Can achieve secant method, Newton method, iterative method, parabolic root)