coderesult

说明：  应用于fluent的UDF程序，用于修正液滴表面轮廓(The UDF is applied fluent procedures for correcting the droplet surface contour)

一种特殊的小波图像处理与图像融合技术,可以用于处理图像加密(a wavelet image transform and image code)

多聚焦图像融合代码，主要包含了方差法和最大系数法融合(Multi-focus image fusion code, mainly includes the variance method and the maximum coefficient fusion)

用对偶分裂算法处理乘性噪声如盐椒噪声（L1+TV），参数由电脑自动选取，matlab程序(A Duality-Based Splitting Method for L1-TV Image Restoration with Automatic Regularization Parameter Choice)

基于曲波变换，小波变换的图像融合，图像检测的相关文献，有期刊，也有硕士论文，中文英文都有，都是近几年的文章，供大家参考学习(Based on curvelet transform, wavelet transform image fusion, image detection literature, there are journals, but also master' s thesis, Chinese, English has, in recent years are the article, for your reference learning)

直方图均衡化处理编程指南及实验报告，数字图像处理及应用，阮秋琦教授，北京交通大学（资源分享）。(Histogram equalization processing programming guide and laboratory reports，Application of digital image processing and Beijing Jiaotong University, Professor Ruan Qiuqi)

dib图像的读取，显示以及存储，能够运行(dib image read, display, and storage, and be able to run)

实现LLE算法，本算法是改进的LLE算法，主要是针对人脸图像的。()

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

Retinex算法，用于图像增强。 包括全局域retinex 局部域SSR、MSR、MSRCR(Retinex algorithm for image enhancement. Including full local retinex local domain SSR, MSR, MSRCR)