sfun_mppt_inc

用于SAR图像识别与分类的官方MSTAR图像集，百度云链接，永久有效，2GB。(Official MSTAR image set for SAR image recognition and classification, Baidu cloud link, permanently valid, 2GB.)

Pre-stack migration applied to GPR for landmine detection

最完整的CCA典型相关分析程序，分析两幅图像，相似度，匹配，融合都可以使用，分析天气变量也可以使用。(The most complete CCA canonical correlation analysis program, analysis of two images, similarity, matching, fusion can be used, analysis of weather variables can also be used.)

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.)

求取相机响应函数，并绘制相对曝光量-灰度曲线(Camera response function, and draw the relative exposure- gray curve )

基于IHS的图像融合算法,用高分辨率图像替换I分量(Based on the IHS image fusion algorithm using high-resolution images to replace I-component)

遥感影像处理，可以用于盲源信号分离，快速高效的独立成分分析方法(Remote sensing image processing, can be used for blind source separation, rapid and efficient method of independent component analysis)

说明：  实现了平移、缩放、旋转和错切等仿射变换的问题，并用MATLAB逼真模拟了蕨类叶、变形蕨类叶与拟仿射变换分形图。(Achieved a pan, zoom, rotate and cross cutting issues such as affine transformations, and use MATLAB to simulate real fern leaf, fern leaves and to be deformed affine fractal images.)

说明：  将像素点划分为超像素，便于进行图像处理！(Implementing superpixel segmentation)

说明：  ：在深海采矿环境中超声波传输介质里存在着大量气泡、扰动沉积物、机械噪声等背景噪声与混响，导致有用信号与高 噪声信号迭加在一起，严重影响了测距精度。采用小波分析方法将超声回波信号进行3层小波分解，适当设置门限阈值对小波 系数进行处理，然后对信号进行重构，有效地抑制了信号中噪声对测量精度的影响。研究结果表明：小波方法有很好的降低回 波信号中噪声的效果，其测距精度高于自适应滤波去噪后的测距精度。(There are much background and mixture noise in the course of ultrasonic wave transmission under deep sea mining environment，such as air bubbles and disturbed sediment and mechanical noise．Because of these factors， the useful signals and the high noise signals are combined together，which seriously affects the distance measurement precision．Ultrasonic echo signals are decomposed into three layer wavelets，and a threshold is set to process the wavelet coeficients．Then the signals are reconstructed．Accordingly the influence of environment noise on distance measurement precision is effectively restrained．Research resuhs indicate that wavelet transform method is very useful for noise reduction in signals．Its precision is higher than that of the adaptive filtering method．)