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IDL编程：tif图像批量layerstacking，并保留原有地图投影。使用时只需要修改输入和输出路径。(IDL programming: tif image batch layerstacking, and retain the original map projection. Only need to modify the input and output paths use.)

傅里叶变换及其逆变换的基于VC6.0实现(Fourier transform and its inverse transform)

张正友标定法,标定图像，将图像进行校正，是当今用的最多的方式方法(This method is so good, I have transferred through this. And it is very useful for the IT workers. This is my first code. Thank you every one.)

说明：  压缩感知的经典代码，包括观测，稀疏表示，重建，其中观测用的高斯观测矩阵，稀疏用的DCT，重建用的OMP算法(Compressed sensing of the classic code, including observations, sparse representation, reconstruction, observed with a Gaussian observation matrix, sparse use of the DCT, re-use of the OMP algorithm)

将某一8位的raw格式图转换为16位的raw格式图 并可输出raw格式图的灰度值至相应文件（.txt文件） 生成的新图用PS打开时与原图基本一致.(It can converted an 8-bit raw format, to an 16-bit raw format and can output raw format diagram of the gray value to the corresponding map file (. Txt files) .The new plan to open with PS are basically consistent with the Original.)

基于C++的人脸分割的设计，C／Ｃ++语言、数字信号处理，最好选修过“数字图像处理”。(Based on the C++ face segmentation design, C/C++ language, digital signal processing, the best elect digital image processing.)

vc获取指定文件的图标的程序源码，希望对大家有所帮助(vc for the specified source file' s icon in the program, we hope to help)

双目立体匹配，使用SAD，SSD，NCC算法，比较多种常见算法的优劣，对其优化实现快速准确匹配。(Binocular stereo matching, the use of SAD, SSD, NCC algorithm, compare the merits of a variety of common algorithms, and its optimization to achieve fast and accurate matching)

一种简单高效地基于压缩感知的跟踪算法。首先利用符合压缩感知RIP条件的随机感知矩对多尺度图像特征进行降维，然后在降维后的特征上采用简单的朴素贝叶斯分类器进行分类。该跟踪算法非常简单，但是实验结果很鲁棒，速度大概能到达40帧/秒(A simple and efficient tracking algorithm based on compressed sensing. Firstly, with the random sensing matrix compressed sensing RIP conditions for multi-scale image feature dimension reduction, and then use the naive Bias classifier simple classification in the feature reduction after the. The tracking algorithm is very simple, but the results are robust, speed can reach 40 frames per second)

1、参数初始化； 2、形成边界削波数据； 3、波场初始化； 4、Zmax层波场延拓到深度Zmax-1； 5、Zi+1层波场延拓到深度Zi； 6、重复5，从Iz Nz-1开始，直到Iz 1，得测线上的频率—空间域波场； 7、频率-空间域波场对频率做反傅里叶变换，得时间-空间波场； (1, parameter initialization 2, the formation of boundary clipping data 3, wave field initialization 4, Zmax layer wave field extended to the depth of Zmax-1 5, Zi+1 layer wave field extended to the depth of Zi 6, repeat 5, starting Iz Nz-1 until Iz 1, the frequency of the test line- spatial domain wave field 7, frequency space domain wave field to frequency inverse Fourier transform, time- space field )