LaoDazhongbasisofvariations

说明：  利用matlab实现不同曝光成度的图像融合，matlab实现HDR功能(Using matlab to realize image fusion with different exposure degrees, and using MATLAB to realize HDR function)

这是sift特征提取源码，详细介绍了算法原理及应用，对图像图形处理专业人员的重要参考价值！(This is the sift feature extraction source, and detailed algorithm and application of important reference value for image and graphics professionals!)

迭代阈值方法进行图象分割的函数,有测试程序和图片(threshold iterative method of image segmentation function, test procedures and Photo)

外国人写的图像融合处理工具以及GUI界面 源代码 相信会对你有所帮助(foreigners write image-processing tools and the integration of the GUI interface believe that the source code will help you)

说明：  利用非局部均值的算法对图像做去噪，速度比较快，但效果一般，存在一定局限性(Using non-local mean algorithm to denoise image is faster, but the effect is general and there are some limitations.)

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)

Implementations of image processing algorithms(This project can be built by Visual Studio 2012. Project description file included. Currently it is for Windows only.)

对输入的图像帧感兴趣区域进行逆透视投影变换，得到俯视图。(The input of the image frame of interest in the area of the inverse perspective projection transform, get a top view. InversePerspectiveMapping)

实现SURF特征点描述子算法，并使用Oxford Dataset图像自动进行精度评价(SURF feature descriptor and matching precision evaluation)

实现对图像的经验模态分解，得到经验模态分解后的第一层IMF分量，反映了图像的主要信息，去除冗余信息，为识别提供了基础。(Empirical mode decomposition of image, obtain the empirical mode decomposition of the first layer of IMF component, reflected the main information of the image, to remove redundant information, provide the basis for identification. )