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运动模糊图像 图像复原 维纳滤波复原 逆滤波复原 VC++6.0程序 代码(Motion-blurred image restoration image restoration Wiener filtering inverse filtering to recover VC++ 6.0 code)

基于OpenCV实现的图像切割程序，通过程序中参数设置分块的数量和大小(The project is uesd to break an image into block)

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)

本程序是实现图像处理的关于调色板的设置功能。(This program is a set of image processing functions on the palette)

傅里叶变换：采用VC++编写，实现二维图像的傅里叶变换(Fourier Transform: The VC++ prepared to achieve the two-dimensional Fourier transform of the image)

本程序实现功能： 1、微机、IBM工作站segy格式文件的a)变面积、b)波形、c)波形加变面积显示； 2、AGC自动均衡显示； 3、用任意多边形选择剖面数据并提取归一化能量、修改选取数据。 (This program function: 1, microcomputer, IBM workstations segy format file of a) become area, b) waveform, c) waveform and become area shows 2, AGC automatic equilibrium display 3, with arbitrary polygon choose profile and extracted data normalization energy, modify, select data.)

基于meanshift/camshift的视频运动目标跟踪实现，通过鼠标手动选择跟踪目标。基于HSV空间模型，可手动调节H S V的阈值，显示前景、背景、反响投影图。开发工具是VS2008、OPENCV.(Based meanshift/camshift video moving target tracking achieved manually using the mouse to select the target track. HSV space model, you can manually adjust the threshold HSV, showing foreground, background, reaction projection. Development tools are VS2008, OPENCV)

1.打开左右两张影像2.Harris算法提取同名点3.显示提取同名点（若要进行下一步匹配则不建议显示，这里只是用于查看是否提取出）4.相关系数匹配（只在找出的同名点内匹配）5.LSM最小二乘匹配（先进行粗匹配，再精匹配）(1 Open the left and right images 2.Harris algorithm to extract two tie points 3 shows the extraction of corresponding points (not recommended to proceed to the next match show, here is used to see if extracted) 4. Correlation coefficient matching (just looking match within a point of the same name) 5.LSM least squares matching (rough first match, then fine match))

2016华为软件精英挑战赛，采用迪杰斯特拉算法，效率高，但需要自行修改(HUAWEI software challenge 2016)

基于SIFT特征的遥感影像自动配准.rar (SIFT-based remote sensing image characteristics of automatic registration. Rar)