CVPR12_SAS_code

模拟闪变仪，用于检测电压波动与闪变，满足IEC推荐的平方检测法。(Analog Flickermeter for detecting a voltage fluctuation and flicker, meet IEC square detection method recommended.)

边缘检测，并分割，以不同颜色标示。站内有其matlab实现，这是对应的c++代码。(Edge detection and segmentation, marked with different colors. Inside the station are the matlab realize, This is corresponding c++ code.)

立体视觉代码。主要过程包括：harris角点检测，zncc最优策略匹配，扩散得到更多特征对应，计算disparity和对应颜色值。另外提供了两幅图片以及对应的特征匹配的结果和disparity图像。(Three-dimensional visual codes. The main process includes: harris corner detection, zncc optimal strategy for matching, the proliferation of more features of the corresponding calculation of disparity and the corresponding color value. Also provides a picture and two corresponding feature matching results and disparity images.)

基于模糊对比度的图像增强方法，大致过程仍然是先把图像从空间域映射到模糊域，在模糊域内通过定义一个局部对比度算子，然后通过对凸函数的加强来放大像素邻域的各像素之间的差异。 (Based on the fuzzy contrast image enhancement method, the general process is still the first images from space domain is mapped to the fuzzy field in fuzzy field through the define a local contrast operator, and then the convex function to enlarge the strengthening of pixels each neighborhood pixel differences. )

使用matlab对图像进行超像素分割，附带可执行程序。(Using MATLAB for ultra pixel segmentation of the image, accompanied by executable program.)

说明：  为图像分别加高斯噪声和椒盐噪声，采用中值滤波方法对受噪声干扰的图像滤波，窗口分别采用3*3,5*5,7*7；(Gaussian noise and salt and pepper noise are added to the image respectively. The median filtering method is used to filter the image disturbed by noise. The window is 3 * 3,5 * 5,7 * 7;)

该代码，利用GDAL 1.4.2库实现遥感图像的几何校正、图像配准等，vs 2010实现。(The code GDAL 1.4.2 library implementation of remote sensing image geometric correction, image registration, vs 2010.)

图片的旋转、截图、灰度、翻转、滤波、去噪等基本处理(Image rotation, screenshots, gray, flip, filtering, noise and other basic processing)

传统滤波方式如均值滤波，中值滤波，维纳滤波对图像去噪的处理以及自适应中值滤波对图像去噪。(Traditional filtering methods such as mean filtering, median filtering, wiener filtering for image denoising processing and adaptive median filter for image denoising.)

这是SPAMS的原始代码，是稀疏表示的重要工具箱~(This is SPAMS original code, is an important toolbox sparse representation)