CRF2D

说明：  一系列关于图像处理的matlab常用源码合集(A collection of common source codes about image processing of MATLAB)

基于opencv 实现毛衣的瑕疵检测 属于毕业设计 功能完整(it is perfect)

卷积神经网络（Convolutional Neural Network）是一个专门针对图像识别问题设计的神经网络。它模仿人类识别图像的多层过程：瞳孔摄入像素；大脑皮层某些细胞初步处理，发现形状边缘、方向；抽象判定形状（如圆形、方形）；进一步抽象判定（如判断物体是气球）。(Convolutional neural network is a neural network specially designed for image recognition. It imitates the multi-layer process of human recognition image: pupil ingestion of pixels; some cells in the cerebral cortex preliminary processing to find shape edges and directions; Abstract judgment of shape (such as circles and squares); and further Abstract judgment (such as judging objects are balloons).)

说明：  图像融合是图像处理的一个研究热点，这里提供一种方法即局部能量最大选取规则图像融合法(Image fusion is image processing of a research hot spot that is here to provide a way to select the rules of the local energy of the largest image fusion method)

第二代Curvelet变换及其在图像融合中的应用研究，第二代Curvelet较第一代有更好的发展前景(Second-generation Curvelet Transform and Its Application in Image Fusion of applied research, the second-generation Curvelet better than the first generation of the development prospects of)

采用的是基于弦中点的hough变换椭圆检测算法，大家可以在百度上搜这篇论文，由于不是用的标准hough变换的算法，所以运行速度还不错(Used is based on the midpoint of the chord hough transform ellipse detection algorithm, we can search on Baidu paper, because the algorithm is not used in standard hough transform, so the speed is also good)

基于格子玻尔兹曼方法模拟泊肃叶流，边界条件用非平衡格式(Poiseuille flow based on the lattice Boltzmann method to simulate the boundary conditions with unbalanced format )

This code implements two variations of the paper "High accuracy optic flow using a theory for warping" presented at ECCV 2004 by Dr. Thomas Brox.

不均匀光照下的文字分割，综合运用同态滤波方法、Bernsen局部阈值法、边缘识别法。(Uneven illumination of the text segmentation, integrated use of homomorphic filtering methods, Bernsen local threshold, the edge identification method.)

基于小波变换的图像融合程序，低频采用加权平均，高频采用能量最大准则。(Based on wavelet transform image fusion program, low-weighted average, using high-frequency energy is the biggest criteria.)