baizhaosheng

一个阈值去噪程序，包括经典的去噪方法，如折中阈值，自适应阈值等等。(A threshold denoising procedures, including the classical denoising methods, such as compromise threshold, adaptive threshold and so on.)

基于阴影形成的原理及阴影区域的特点，研究阴影区域的特征表示方法； 基于阴影区域特征设计或改进阴影检测方法，检测出户外图像中的阴影区域； 在检测出阴影区域的基础上，研究阴影去除方法； 编程实现相关方法并进行实验验证及分析。(Shadow detection and removal of single image)

水平集(level set)的基本思想是将界面看成高一维空间中某一函数ψ（称为水平集函数）的零水平集，同时界面的演化也扩充到高一维的空间中。我们将水平集函数按照它所满足的发展方程进行演化或迭代，由于水平集函数不断进行演化，所以对应的零水平集也在不断变化，当水平集演化趋于平稳时，演化停止，得到界面形状。(The level set (level set) the basic idea is to interface as a higher dimensional space in a function (called a level set function) of the zero level set, and the interface evolution also extended to higher dimensional space. We evolve or iterate the level set function according to the evolution equation it satisfies. Because the level set function keeps evolving, so the corresponding zero level set is also changing. When the level set evolves to a stable state, the evolution stops, and the interface shape is obtained.)

关于高光谱图像的图像处理技术，RX异常检测技术，代码功能强大，且代码注释很多，对学习很有帮助。(Hyperspectral image on image processing techniques, RX Anomaly Detection technology, powerful code feature, and many code comments, learning helpful.)

自己编的改进谐波小波包实现程序，实现了信号经过谐波小波包变换后幅值不变，适合于机械故障特征提取(The own series improved harmonic wavelet packet achieve signal amplitude unchanged after harmonic wavelet packet transform, for mechanical fault feature extraction)

提取GIST特征的matlab实现源码，初学者实用(Extract GIST features matlab achieve source beginners practical)

说明：  利用GMS对特征点匹配进行约束，降低误匹配率，代码包含python版本，C++版本，matlab版本。(GMS is used to constrain the matching of feature points to reduce the error matching rate. The code includes Python version, C + + version and Matlab version.)

对图像进行处理，利用拉普拉斯锐化进行边缘检测。(The image is processed and the edge is detected by Laplasse sharpening.)

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)

开发的可将扫描获得点云数据 生成nurbs曲面的小程序(Development can be scanned point cloud data generated nurbs surfaces of the small programs)