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建立一个透明物体上有污点的模型，可以模拟玻璃上有污点的图象(Rendering of clean transparent objects has been well studied in computer graphics. However, real-world transparent objects are seldom clean—their surfaces have a variety of contaminants such as dust, dirt, and lipids. These contaminants produce a number of complex volumetric scattering effects that must be taken into account when creating photorealistic renderings. In this paper, we take a step toward modeling and rendering these effects. We make the assumption that the contaminant is an optically thin layer and construct an analytic model following results in radiative transport theory and computer graphics. Moreover, the spatial textures created by the different types of contamination are also important in achieving visual realism. To this end, we measure the spatially varying thicknesses and the scattering parameters of a number of glass panes with various types of dust, dirt, and lipids. We also develop a simple interactive synthesis tool to create novel instances of the me)

高斯滤波算法，可用于模糊图片，除掉图片中的高频噪声(gauss fliter to remove high frequency noise for pic )

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)

Image Database 2.5.0 (w/ thumbnails)

读取图像，将RGB图像转化为灰度图像，显示并保存(The RGB image is transformed into gray image)

多类 kmeans 图像分割，基于灰度的图像分割。(Kmeans image segmentation, segmentation based on gray-scale images.)

光流法、帧间差分法、高斯背景模型差分法，在opencv环境下实现运动目标检测(moving objective detection matlab)

图像平移处理，可以图片进行平移变换处理，提供演示图片(Image translation process, it can image pan transformation process provides demonstration image)

说明：  能精确的提取数字图像的轮廓。不管图形的形状如何，都能达到预期的效果。并且能将边界的坐标输出到一个文件中，供使用者分析数据。(Able to extract precise contours of the digital image. Regardless of the shape of how graphics can achieve the desired effects. The coordinates of the border and is capable of output to a file, for users to analyze data.)

图像分割经典算法GraphCut的实现代码，亲测可用。(An implementation of GraphCut Algorithm, which is a classical method in image segmentation field.)