VisualSFM_windows_cuda_64bit

bmp文件的读取,2,8,16,24bit自适配(bmp file read,2、8、16、24bit adjust)

自己编写的数字图像处理程序，包括打开bmp图像，直方图，阈值分割，形态学处理等功能。(digital image processing procedures, including open bmp image, histogram, threshold segmentation, morphological processing and other functions.)

对图像进行平滑去噪，提高图像的质量，为后期的图像处理打基础(very good)

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)

三维最大Renyi熵的灰度图像阈值分割算法(Maximum Renyi entropy of three-dimensional gray-scale image segmentation algorithm)

用CUDA并行处理方法改写的图像降噪算法，包括KNN,NLM,以及改进的NLM方法。配置环境适合VS2010+CUDA5.0,对使用CUDA的同学来说是很好的教材。(Image denoising algorithms including KNN,NLM and refined NLM run on CUDA, useful demo for who learns CUDA based parallel programming.)

暗通道去雾代码，使用c++实现 根据cvpr论文改写(Channel code to the dark fog)

连续投影算法的Matlab程序 下载后可以直接使用(Successive projections algorithm )

VB像素光影跟踪（图像渲染）工具,有需要的就下载吧。(VB Tracking pixel lighting (image rendering) tools, there is a need to download it.)

用于图像拼接的素材，可用于全景图拼接。主要是JPG形式，可通过SIFT算法进行处理(Material for image stitching, can be used for panorama stitching. Mainly JPG format, can be handled by the SIFT)