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图像去雾 暗原色 导向滤波 最好的去雾算法 何恺明的matlab代码的opencv的实现(haze removal guided image filtering the best algorithm to fog )

PMF FFT捕获技术性能仿真，分段匹配滤波法和改进算法相比较(FFT PMF capture technology performance simulation, segmented matching filter and improved algorithm comparison)

说明：  行人检测HOG+SVM进行图片中行人检测，提供训练用的pos和neg样本，效果还可以；没有SVM工具箱的，压缩包里已经提供了，安装一下即可(Pedestrian detection HOG + SVM for pedestrian detection in pictures, providing POS and neg samples for training, the effect is good; without SVM toolbox, the compression package has been provided, just install it.)

运用于人脸图像预处理中，主要实现功能有：人脸检测，人脸对齐，人脸图像放缩，人脸剪切。(Applied to the face image preprocessing, the main features are: face detection, face alignment, face image zoom, face cuts.)

矢量区域填充算法（包括汉字提取生成） 算法(Vector area filling algorithm (including the extraction of Chinese characters generated) algorithm)

图像算法开放库，对图像处理的，希望对学习者有所帮助！(Image algorithm open library of image processing, and they hope to help learners!)

基于OPENCV的SIFT特征提取与匹配算法。包含完整的从图像高斯金字塔、DOG、空间极值点提取、关键点描述、KDtree匹配等关键步骤的全部函数实现，对全面深入理解Lowe的SIFT算法有莫大帮助。程序运行前须安装（1）OpenCV: http://opencvlibrary.sourceforge.net （2）SIFT: http://web.engr.oregonstate.edu/~hess/index.html，并配置其环境参数。(OPENCV the SIFT-based feature extraction and matching algorithm. Contains a complete Gaussian pyramid from the image, DOG, space extremum point extraction, description of key points, KDtree matching key step in the realization of the full function of the comprehensive and in-depth understanding of Lowe s SIFT algorithm of tremendous help. Program to run before the installation of (1) OpenCV: http://opencvlibrary.sourceforge.net (2) SIFT: http://web.engr.oregonstate.edu/ ~ hess/index.html, and configure the parameters of their environment.)

说明：  线形骨架的综述类文献，着重强调定义属性和应用(Curve-skeleton properties, applications, and algorithms)

指纹图像处理包括梯度处理、方向场处理、平滑处理、智能增强处理等(The fingerprint image processing including gradient processing, direction field processing, smooth processing and intelligent enhancement processing, etc)

GraphCut算法的实现，跟踪主动镜头下的目标，效果很好！(GraphCut algorithm to track the goal of the initiative under the lens, very good!)