自适应分数阶微分法 fractional differential

对图像进行滤波，顶帽变换并计算中心，有图片，可直接运行。(The image filtering, top-hat transform and Computing Center, there are images which can be directly run.)

说明：  对图像提取同名点，并根据同名点建立delaunay三角网，后续可进行图像配准，或根据三角网进行控制点筛选(The same name points are extracted from the image, and the Delaunay triangulation network is established according to the same name points. The image registration can be carried out later, or the control points can be selected according to the triangulation network)

单尺度SSR(Single Scale Retinex)(A Retinex Function)

说明：  ：基于主动轮廓识别和被动轮廓识别方法各自的优缺点，提出结合主动和被动的方法，先对图像进行被动轮廓的预处理，然 后再应用主动轮廓的方法，通过比较选出Canny算子进行预处理，再通过基于概率的方法分割图像，最后再应用Snake模型进行 轮廓提取。并取得较好的应用。(: Identification Based on Active Contour and passive contour recognition advantages and disadvantages of each method, proposed method of combining active and passive, passive first outline of the image pre-processing before applying the active contour method, by comparing the pre-selected Canny operator treatment, and then through the image segmentation method based on probability, and finally application of Snake model for contour extraction. And get better application.)

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.)

本程序是基于图论的知识进行图像分割，其中用到的是graphcut分割知识，完整的程序代码及结果！！(This procedure based on the knowledge of graph theory for image segmentation, which is used graphcut segmentation knowledge, including program code and the complete results !!)

Diff-rankboost算法,代码功能是产生图片美学质量之间相互的排名差距，便于进一步的进行训练和测试(Diff-rankboost algorithm, code function is to produce the ranking of mutual aesthetic gap between picture quality, ease of further training and testing)

说明：  图像预处理，灰度化，滤波，将图像输入后经过算法得到灰度图，然后进行后续一系列转化，拟合圆和椭圆曲线(Image preprocessing, graying, filtering)

不规则窗体

图像融合的各种方法，包括IHS变换，PCA变换，小波变换等等(Various methods of image fusion, including IHS transform, PCA transform, wavelet transform, etc.)