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L0梯度最小化算法，2011年由xuli提出的算法(L0 gradient minimization algorithm, in 2011 xuli put forward the algorithm )

图割（GC)和主动轮廓模型（ACM)相结合的一种图像分割方法，既可以进行局部图像的分割，也可进行全局图像的分割，简单实用。(A combination of graph cuts (GC) and the active contour model (ACM) image segmentation method, either local image segmentation, global image segmentation, simple and practical.)

人脸识别源代码，分为人脸检测，人脸识别等几部分(Face recognition source code, is divided into face detection, face recognition and other parts)

去散射和边缘增强是水下图像从严重细节损失、颜色偏移和模糊中提取的关键步骤。本文提出了一种增强水下图像对比度和边缘的新方法。(De-scattering and edge enhancing are critical procedures for underwater images which surfer from serious detail loss, color deviation and blurring. In this work, a novel method has been proposed to enhance contrast and edge of underwater images.)

本文提出了基于Retinex可变框架模型的图像增强算法。实验证明该算法不但能有效的增强图像的质量，还能避免Retinex算法中带来的光晕效应，同时算法速度与同类型的图像增强算法比较更快速。之后，将这种理论运用到对彩色图像增强中，取得了很好的处理效果。 （使用同方知网浏览器打开）(This paper presents a framework model based on variable Retinex image enhancement algorithm. Experiments show that this algorithm not only can effectively enhance the image quality, but also to avoid the Retinex algorithm brought halo effect, and algorithm speed and the same type of image enhancement algorithm is relatively faster. After this kind of theory to the enhancement of color images, achieved good treatment effect. (Text browser to use the same side open))

基于小波和形态学的自然地面背景红外目标检测方法。。。。。。(Based on wavelet and morphology of the natural terrestrial background infrared target detection method)

EDLines是一种快速直线检测算子，2012年在ICCV上提出，也是目前处理直线检测最快的算法之一，该算法包含三个步骤：（1）边缘提取：利用Edge Drawing (ED)算法[28,29]从灰度图像中提取边缘片段；（2）线段检测：利用最小二乘法提取直线段；（3）线段确认：遵循Helmholtz定律，从已提取的直线段中摒弃虚假线段。EDLines算法的优越性得益于Edge Drawing (ED)算法能够从灰度图像中准确、快速、稳定地提取出光滑、完整的边缘片段。Edge Drawing (ED)算法包含以下步骤： （1）采用size=5*5,σ=1的高斯核对灰度图像进行平滑滤波，去除噪声； （2）采用一种常用的梯度算子，如Prewitt、Sobel或Scharr等计算平滑后图像中每个像素点的梯度幅度和梯度方向； （3）将梯度图中邻域内幅度最大的像素点标记为锚点，这些锚点成为图像边缘点(edge elements)的概率很大； （4）将相邻的锚点连接成边缘线。从一个锚点起始，ED利用相邻像素的梯度幅度和方向在梯度为最大值的锚点之间游走。 (Edge Drawing (ED) is our recently-proposed, novel, fast edge detection algorithm. What makes ED stand out the existing edge detectors, e.g., Canny, is the following: While the other edge detectors give out a binary edge image as output, where the etected edge pixels are usually independent, discontinuous entities ED produces a set of edge segments, which are clean, contiguous, i.e., connected, chains of edge pixels. Thus, while the output of the other edge detectors requires urther processing to generate potential object boundaries, which may not even be possible or result in inaccuracies ED not only produces perfectly connected object boundaries by default, but it also achieves this in blazing speed compared to other edge detector.)

说明：  该代码是图像处理中块匹配的全搜索算法，是用来估计和计算运动矢量的。(The image processing code is the full search block matching algorithm is used to estimate and calculate the motion vector.)

亚像素角点定位函数代码,输入参数为角点像素级粗略坐标,输出精确的亚像素级角点坐标(corner subpixel positioning function code, the input parameters for the corner pixel rough coordinates, Output precision Subpixel corner coordinates)

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)