RANSAC-for-Outlier-Rejection

2009年CVPR最佳论文,何恺明的基于暗通道的图像去雾的相关论文，ppt以及matlab代码. Dark channel prior 是一种对无雾的图像的统计规律：在无雾图像中，大部分图像块中至少有一个颜色通道具有很小的颜色强度值。利用dark channel prior，可以直接从一幅有雾的图像中估计出雾的浓度，并恢复出高质量的去雾图像。(CVPR best paper in 2009 (He Kai Ming Single Image Removal Haze is the Using the Dark Channel) paper, ppt and the matlab code, it is)

一个经典的动态视频图像去隔行处理的源代码,能消除双场图像的场效应(A classic dynamic de-interlacing video processing source code, to eliminate dual-field image of the field-effect)

SSR单尺度图像增强 MSR多尺度Retinex图像增强模型(MSR Multiscale Retinex Image Enhancement Model)

医学图像处理MRI脑仿真库BrainWeb，mnc格式文件的读取代码。(The reading code of mnc format file,for MRI medical image processing Brain simulation library BrainWeb.)

摘　要:舌象中的裂纹是中医舌诊中的重要内容。由于拍摄条件的不同,舌象质量有较大差异,传统的阈值选取方法并不 适用。文中提出一种舌象裂纹检测的自适应阈值选择方法。该方法利用舌象的L 3 a 3 b 色彩特征及区域的分裂- 合并, 对舌象进行区域分割,自适应地选取舌中部区域的色彩值作为阈值,对整个舌象进行裂纹提取。经验证,本方案对不同的 舌象能较好地提取出裂纹,实现舌象裂纹诊断的客观化。(Tongue’ s crack is a very important part of herbalist doctor diagnosis. For the different screen conditions , there are many differ2 ences on the tongue’ s quality. It is not effective to use the t raditional threshold ext raction algorithm. In order to solve this problem , pro2 pose a new adaptive threshold algorithm. Present the segmentation of the image of tongue by using the feature on tongue in the L 3 a 3 b color space and the split- combining algorithm. Then use the threshold , which is the color value ext racted automatically in the middle of the tongue , to detect the crack of the whole tongue. The experiments show that this approach is able to distill the crack effectively to different tongue images , and achieve the objectivity of the diagnosis based on the tongue’ s crack.)

这是一个基于matlab语言编写的沃尔什变换程序，里面有一个4X4的矩阵可当例子，修改相关参数可用于2^n的矩阵(Walsh Transform matlab language based program, which has a 4X4 matrix when the example 2 ^ n matrix can be used to modify the relevant parameters)

CT模型仿真，里面有C还有Matlab文件，均可以使用(CT model simulation with C and Matlab)

基于椒盐噪声滤波的改进加权中值滤波算法,目的在于处理高浓度椒盐噪声，并且有效的保护边缘细节(salt and pepper noise filter and weighted)

实验两张图片的拼接，对于图片中的匹配对，用ransac方法消除错配，并估计出仿射矩阵。然后将一张图进行仿射变换，再实现拼接(Experiment two pictures of the stitching, matching pairs for the picture, with ransac way to eliminate mismatches, and to estimate the affine matrix. Then an affine transformation diagram, and then realize splicing)

很简单的基于颜色的图像检索系统，闲时做的(Very simple color-based image retrieval system at leisure to do the)