L0330

说明：  注：运行前自己准备图像，修改I = imread('')单引号中的路径 1. 给一张灰度图添分别添加高斯噪声和椒盐噪声。然后分别进行均值滤波和中值滤波，并把处理后的图片保存。 2. 图像频域处理，对图像进行傅里叶变换，进行高通滤波，显示处理结果。 3. 图像平移和旋转 4. 分别用OSTU阈值法和全局阈值法分割图像，然后进行腐蚀和膨胀处理，显示处理结果。(Note: Prepare the image by yourself before running, modify the path in single quotes of I = imread('')1. Add Gaussian noise and salt and pepper noise to a grayscale image. Then perform mean filtering and median filtering respectively, and save the processed pictures.2. Image frequency domain processing, Fourier transform of the image, high-pass filter, and display the processing result.3. Image translation and rotation4. Separate the image with OSTU threshold method and global threshold method, and then perform corrosion and dilation processing, and display the processing results.)

IDL程序，采用光谱融合法对遥感影像进行去云处理。(IDL procedures, the use of spectral fusion of remote sensing images to cloud processing.)

经典主成分分析法，实现高光谱图像的降维处理 (Classical principal component analysis, to achieve high spectral image dimensionality reduction)

采用harris角点特征完成图像拼接，包含特征点的选取以及最终拼接后的结果输出(Harris corner feature complete image stitching, contains the feature points selected and the resulting output after final stitching)

这是一个实现边缘连接的程序，用于连接在一条轮廓线上的边缘点(edge link)

读取MODIS的HDF文件和ENVI IDL的程序(MODIS ENVI IDL readhdf.pro)

对于传统去噪模型的大幅改进，之前的模型都会出现阶梯效应的现象，采取了新的模型对图像进行建模，有效改善了图像去噪图像修复等过程中引入的阶梯效应，而且一定程度上对于图像纹理的修复也有很大的作用(For significantly improve the traditional de-noising model, the model will appear before the phenomenon of the staircase effect, to take a new model for image modeling, effectively improved the staircase effect denoising image restoration process introduced, and to a certain extent for texture of repair also has a significant role)

说明：  sift算法实现的图像匹配程序，使用matlab编写的，多用于图像拼接，融合等领域。(The image matching program implemented by SIFT algorithm is written by MATLAB, and it is mostly used in image splicing, fusion and other fields.)

双目视觉经验总结，希望后面的不要犯错误。(Binocular visual experience summary, make no mistake behind.)

log Gabor小波图像纹理特征分析我小改過(log Gabor wavelet texture features of image I have little turn over)