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三维激光点云配准是点云三维建模的关键问题之一。经典的 ICP 算法对点云初始位置要求较高且配准 效率较低，提出了一种改进的 ICP 点云配准算法。该算法首先利用主成分分析法实现点云的初始配准，获得较好 的点云初始位置，然后在经典 ICP 算法的基础上，采用 k － d tree 结构实现加速搜索，并利用方向向量夹角阈值去除 错误点对，提高算法的效率。实验表明，本算法流程在保证配准精度的前提下，显著提高了配准效率。 (Three-dimensional laser point cloud registration is one of the key three-dimensional point cloud model. High classical ICP algorithm to the initial position of the point cloud registration requirements and low efficiency, proposed an improved ICP point cloud registration algorithm. Firstly, the use of principal component analysis of the initial point cloud registration, get a better initial position of the point cloud, then the basis of classical ICP algorithm using k- d tree structure to achieve speed up the search, and using the direction vector angle the removal of the threshold point error and improve the efficiency of the algorithm. Experiments show that the algorithm processes to ensure the accuracy of registration under the premise, significantly improve the efficiency of registration.)

利用DCT字典对图形进行稀疏表示，实现两幅图像的融合(Using the DCT dictionary to sparse representation of the graphics to achieve the fusion of two images)

数字图像处理有关的论文，很优秀，很有指导意义的一篇论文。(Digital image processing the papers, very good, very instructive paper.)

hough变换的图像倾斜校正的matlab源码，图像预处理的重要环节之一。(hough transform image tilt correction matlab source, an important part of image pre-processing one.)

两张图片相减 散斑干涉图像获取 Two image subtraction Two image subtraction(Two image subtraction Two image subtraction Two image subtraction)

这是一个利用matlab开发的程序，功能是用susan算法提取图像角点的。一个压缩包，程序可用哟。(This is a program developed using matlab, the functional algorithm is susan corner of image. A compact package, the procedure can be used yo.)

基于差值的可逆水印算法源码，及详解说明。还包括一篇英文论文和该作者的一些理解和解释，希望对大家有帮助(Reversible watermarking algorithm based on difference of source code, and the Detailed Description. Also includes an English papers and some of the author' s understanding and interpretation, we hope to help)

Image processing using sobel operator

说明：  SOM工具包，包括matlab程序及学习文档(SOM toolkit, including the procedures and learning matlab documentation)

Show how to use unsharp masking algorithm. No image processing toolbox is needed.