GMM

利用最大类间方差算法求取自动阈值，实现图像分割(Using the maximum inter class variance algorithm for automatic threshold, image segmentation)

用于单目标追踪的多模概率假设粒子滤波程序(MM-PHD for single target)

VC中绘制坐标系、网格、常用数学函数以及辅助功能（背景色切换、坐标标题修改等）(vc draw)

基于CFAR虚警率的图像分割算法，可快速对灰度图像进行CFAR检测分割。(Based on the false alarm rate of CFAR image segmentation algorithm, the gray image can be fast CFAR detection and segmentation.)

(l)小波分析理论在变形监测数据处理研究中的理论意义和实用价值 (2)小波阂值去噪和多分辨分析在变形监测信号分析中的应用 (3)在算法和图像处理方面的优越性 ((L) wavelet analysis theory in the study of deformation monitoring data processing theoretical significance and practical value (2) wavelet thresholding denoising and multi-resolution analysis in deformation monitoring signal analysis application (3) in the algorithm and image processing superiority )

用共轭梯度下降算法 求解图像压缩感知 并进行比较(Conjugate gradient descent algorithm for image compression and compared perception)

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.)

集成ITK、VTK、MFC读取DICOM的代码，建成win32程序即可。运行完美(Integrated ITK, VTK, MFC to read DICOM code, built win32 program can. Works perfect)

这是一个MATLAB工具箱包括32个降维程序，主要包括 pca,lda,MDS等十几个程序包，对于图像处理非常具有参考价值！！( ，This Matlab toolbox implements 32 techniques for dimensionality reduction. These techniques are all available through the COMPUTE_MAPPING function or trhough the GUI. The following techniques are available: - Principal Component Analysis ( PCA ) - Linear Discriminant Analysis ( LDA ) - Multidimensional scaling ( MDS ) - Probabilistic PCA ( ProbPCA ) - Factor analysis ( FactorAnalysis ) - Sammon mapping ( Sammon ) - Isomap ( Isomap ) - Landmark Isomap ( LandmarkIsomap ) - Locally Linear Embedding ( LLE ) - Laplacian Eigenmaps ( Laplacian ) - Hessian LLE ( HessianLLE ) - Local Tangent Space Alignment ( LTSA ) - Diffusion maps ( DiffusionMaps ) - Kernel PCA ( KernelPCA ) - Generalized Discriminant Analysis ( KernelLDA ) )

说明：  基于改进JPEG-LS算法的遥感图像近无损压缩专利，由航天五院508所申报，很详细的介绍了算法和fpga的实现(Improved JPEG-LS algorithm near lossless compression patent, the space the five branches of 508 reporting, a detailed explanation of the algorithm and implementation fpga)