jiangcaiyang

自己编写的关于2013年的文章 a variational method for multi-source remote-sensing image fusion 的程序，基本实现了相关功能。(I have written a progrma about a variational method for multi-source remote-sensing image fusion publish in 2013,and the basic functions of the problems have been solved.)

适用于高光谱图像目标检测的端元提取，该方法效果好(HYPERICAEEA Performs the ICA-Endmember Extraction Algorithm HyperIcaEea performs the ICA-EEA algorithm to generate abundance maps and find pure pixels. This function utilizes FastICA.)

说明：  基于python-opencv的图像匹配代码，包含了SIFT、SURF、AKAZE、ORB方法。43-48行修改图像路径，74-81修改匹配方法。(dev: python3.6+opencv_python==3.4.2+opencv-contrib-python==3.4.2)

改进后的非线性各向异性扩散用于图像中的保边去噪，增加了二阶导数，是滤波效果更好(Improved nonlinear anisotropic diffusion for edge preserving image denoising, an increase of second derivative, is a better filtering effect)

说明：  使用Splitting算法和GLA算法实现对图像的矢量量化及重新编码和重建。(Vector Quantization:To generate a 16-codeword codebook using Splitting Algorithm and GLA,then use this codebook to code the training image and reconstuct it.)

图像直方图统计，并生成灰度图。 matlab程序(Histogram of the image statistics, and generate grayscale. Matlab program)

连续投影算法的Matlab程序 下载后可以直接使用(Successive projections algorithm )

提取图像的SURF特征点。包含两个例程，分别为提取到的特征点与特征点匹配(Extract SURF feature points from the image)

利用PCA和模糊C均值相结合的方法实现图象的聚类(Using PCA and fuzzy C-means method of combining images to achieve the clustering)

本程序用于对工件图像的预处理，边缘提取等。将改进遗传算法和Hausdorff距离结合用于工件识别。采用canny边缘为匹配特征，将修正的Hausdorff距离作为相似性度量准则，并应用遗传算法进行最佳匹配的快速搜索，成功实现了目标物体的匹配识别(This procedure used for the workpiece image preprocessing, edge extraction and so on. Will improve the genetic algorithm and Hausdorff distance combination for workpiece identification. Using canny edge for matching characteristics, will be amended Hausdorff distance as similarity measurement criteria and the application of genetic algorithm is the best match of the Quick Search, the successful achievement of the target object matching identification)