read_ENVIimagefile

说明：  基于opencv的支持向量基（SVM）的代码，利用SVM解决2维空间向量的3级分类问题。(Opencv-based support vector machine (SVM) of the code, the use of SVM to solve 2-dimensional vector space of three classifications.)

距离多普勒成像算法，包含运动补偿距离徙动回波构造距离压缩方位压缩(Distance Doppler imaging algorithm, including motion compensation distance migration echo structure compression compression azimuth compression)

利用matlab实现数字图象处理的理想低通滤波器！！(Using matlab to achieve the desired low-pass filter! !)

用lbp实现纹理特征提取，并分类说明: 一共有三个m文件，一个是lbp.m, 存放主要的lbp算法， 一个是getmapping,用以做算法的辅助函数， 一个是lbptest.m,存放着测试代码。 这三个文件需要放到同一个文件夹，并在文件夹中添加相应的图片， 具体的图片名字见lbptest.m的代码，运行lbptest.m可以查看结果。代码最后给出效果图 这三个文件是最传统的LBP方法，有256种。(With lbp achieve texture feature extraction and classification Description: A total of three m files, one is lbp.m, store the main lbp algorithm, One is getmapping, helper functions for doing arithmetic, One is lbptest.m, kept the test code. These three documents need to put the same folder, and add the appropriate folder, pictures, See lbptest.m specific name of the picture of the code, run lbptest.m can view the results. Finally renderings code These three documents are the most traditional LBP method, there are 256 kinds.)

应用条件随机场进行图像分割 使用方法：将pydensecrf-py27或pydensecrf-py35重命名为pydensecrf，放入C:Program FilesAnaconda3Libsite-packages 运行：python inference.py im1.png anno1.png out.png(Renameing the file "pydensecrf-py27" or "pydensecrf-py35" to the new name "pydensecrf" Puting this file "pydensecrf" in this directory "C:Program FilesAnaconda3Libsite-packages" cd examples/ python inference.py im1.png anno1.png out.png)

此算法为基于k-means聚类的非局部均值快速去噪算法，方法便捷有效，可保持边缘信息(this is a fast edge-preserving denoising method based on non-local means method with k-means clustering)

很好的模糊聚类算法 用MATLAB编写的(Good fuzzy clustering algorithm using MATLAB prepared)

说明：  实现手机拍摄图像的二维码图像的提取，包括QR码的旋转与校正，也可以用于其他条码，但是效果不是很好(The realization of mobile dimensional code image captured image extraction, rotation and including a QR code correction can also be used for other bar code, but the effect is not very good)

利用数学形态学对云层背景下的目标进行检测识别，有两种方法。 (Using mathematical morphology of clouds in the context of target identification, there are two ways.)

说明：  adpmedfilt3.m为自适应中值滤波器函数； adpmedfilt3_test.m为利用上述自适应中值滤波器函数进行中值滤波，同时与普通中值滤波器滤波结果对比； 其余为基础图像处理函数； image文件中为实验图像kl.jpg；(adaptive median filter to filt images)