hong_enhancement

基于学习字典的方法进行彩色图像修复 字典学习方法用FastICA(INPAINTING COLOR IMAGES IN LEARNED DICTIONARY )

图像拼接，利用SIFT算法提取点特征，并进行点匹配，解算单应性矩阵，根据结算出的单应性矩阵对图像进行仿射变换，最后进行拼接，程序中的备注很详细，各位感兴趣的同志可以下载看看。(Image mosaic using SIFT feature point extraction algorithm, and point matching, homography matrix solver, based on the settlement of the homography image affine transformation, and finally stitching, very detailed notes in the program, you sense Interested comrades can be downloaded.)

查找图像的局部极大值，功能强大，速度快，精度高(Finding the local maximum of an image is powerful, fast and accurate.)

灰度共生矩阵、灰度梯度共生矩阵提取纹理特征(Gray Level Co-occurrence matrices, gray-gradient co-occurrence matrix texture features extracted)

稀疏矩阵字典的优化KSVD，本人已进行测试，效果甚佳,可以用在图像，数据的压缩和分类(Sparse dictionary optimization KSVD, I have been tested, very good results)

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.)

卷积神经网络深度学习，可以识别多种图像，并自动解出所需要的结果(Deep learning of convolutional neural networks)

基于knn算法的遥感图像分类 源代码 算法测试(Remote sensing image classification based on knn algorithm Source code Algorithm testing)

该程序为直方图均衡化程序，附有GUI界面，操作简单，可现实处理前后图像对比及处理前后的直方图分布情况显示，使用方便。(The program for histogram equalization program, with GUI interface, simple operation, the histogram distribution around the reality that is processing the image before and after treatment, easy to use.)

快速的Lee滤波算法，代码经过优化，修正和测试，能有效减少SAR图像中的斑点噪声。(Fast Lee filter algorithm, code optimized, modification and testing, can effectively reduce the SAR image speckle noise.)