ZHONGBIAOFENGEG

初步的代码，只保存边界的声波逆时偏移 RTM

marburg.c 用Burg算法求AR模型的参数。 mar1psd.c 由AR模型参数得到功率谱。 maryuwa.c 用Levinson算法求解Yule-Walker方程以得到 阶AR模型的参数 。 (marburg.c using Burg algorithm for AR model parameters. mar1psd.c by the AR model parameters obtained power spectrum. Levinson algorithm maryuwa.c with Yule-Walker equation in order to get rank AR model parameters.)

rk3399硬件编解码demo及文档

计算灰度共生距的matlab源代码Haralick Texture Features Matlab Toolbox v0.1b(Calculation of gray symbiotic matlab source code from the Haralick Texture Features Matlab Toolbox v0.1b)

说明：  该代码能够实现K均值聚类算法对彩色图像分割，在MATLAB下实现。(The code can achieve K means clustering algorithm to color image segmentation, in MATLAB to achieve.)

对于视频3D-DWT变换处理,嵌入水印图像。属于数字视频水印算法，包含水印嵌入算法以及水印提取算法。(3DDWT wavelet transform)

通过GDAL读取常用遥感影像，如img，tiff，可实现读取显示和雷达影像处理的一些基本算法(Read through GDAL common remote sensing images, such as img, tiff, read the display and radar can achieve some of the basic image processing algorithms)

通过阈值去噪，最关键的就是要确定最佳阈值T 的大小.如果阈值太小，可以保留更多的小波系数，但同时噪声也被保留；相反，阈值太大，可以消除更多的噪声，但重要图像特征又将被滤掉，引起偏差.目前使用的阈值分为全局阈值和局部阈值.全局阈值对各层所有的小波系数或同一层内的小波系数都是统一的；局部阈值则是根据当前系数周围的局部情况来确定合适的阈值，具有灵活性.(Threshold denoising, the most critical is to determine the optimal threshold T s size. If the threshold is too small, you can retain more of the wavelet coefficients, but the noise was retained the contrary, the threshold is too large, can be eliminatedmore noise, but the important image features in turn be filtered out, causing bias current threshold is divided into a global threshold and local threshold. global Threshold the wavelet coefficients of all the wavelet coefficients of the layers or on the same floorare unity local threshold is based on the local situation of the current coefficient around to determine the appropriate threshold, with flexibility.)

基于形状的模板匹配，用到了opencv，主体包含两部分，建模与金字塔搜索。(Based on the shape of the template matching, the use of opencv, the main body contains two parts, modeling and pyramid search.)

说明：  去除图像中的横向条纹，能有效恢复出原始图像(remove images of horizontal stripes, can be effectively restored from the original image)