shuangmu

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)

基于多帧图像插值（Interpolation）技术的方法是SR恢复技术当中最直观 的方法。这类方法首先估计各帧图像之间的相对运动信息，获得HR图像在非均 匀间距采样点上的象素值，接着通过非均匀插值得到HR栅格上的象素值，最后 采用图像恢复技术来去除模糊和降低噪声（运动估计!非均匀插值!去模糊和 噪声）。(In this paper, we propose a novel method for solv- ing single-image super-resolution problems. Given a low-resolution image as input, we recover its high- resolution counterpart using a set of training exam- ples. While this formulation resembles other learning- based methods for super-resolution, our method has been inspired by recent manifold learning methods, par- ticularly locally linear embedding (LLE). Speci?cally, small image patches in the low- and high-resolution images form manifolds with similar local geometry in two distinct feature spaces. As in LLE, local geometry is characterized by how a feature vector correspond- ing to a patch can be reconstructed by its neighbors in the feature space. Besides using the training image pairs to estimate the high-resolution embedding, we also enforce local compatibility and smoothness con- straints between patches in the target high-resolution image through overlapping. Experiments show that our method is very ?exible )

说明：  recon基于双视图的人脸特征三维重建，一个视图为正投影，另一个是水平方向旋转，假定正交投影模型，getfeature用于从图像上标记特征点(facial feature reconstruction based on two views)

图像超分辨率重建算法，实现图像的超分辨率重建。(super-resolution code )

分别用kmeans、fcm、kfcm实现图像分割(use kmeans, fcm and kfcm segment image)

索书号文字图像分割，粘连字符切分，彩色车牌分割 ，文字识别的结构特征提取子函数(Call text image segmentation, character segmentation, color plate segmentation, text recognition feature extraction Functions)

【实例简介】 云信开源的电子白板，有web、android、ios、qml

说明：  图像融合算法，exercise1:为基于小波变化与局部能量的图像融合方法 exercise2:为基于自适应算法的图像融合算法 myfunction1~myfunction5:为性能指标评价函数(Image fusion algorithm, exercise1: wavelet-based change and the local energy method of image fusion exercise2: adaptive algorithm based on image fusion algorithm myfunction1 ~ myfunction5: performance indicators for the evaluation function)

形态学成分分析，该方法的基本思想是利用信号组成成分的形态差异，将图像分割为纹理和分片光滑部分。(Morphological Component Analysis，The basic point is that an image can be divided into texture and piecewise smooth parts by the morphological diversity among signal components.)

该程序是发表在IEEE上的经典直线提取论文“Extracting Straight Lines”的源代码实现，对计算机视觉、模式识别和信息提取等领域的科学研究人员具有极其重要的参看意义。建议下载学习和适用。(The program is published in the IEEE paper on the classic straight-line extraction " Extracting Straight Lines" the source code implementation of computer vision, pattern recognition and information extraction and other areas of scientific researchers see an extremely important significance. Recommended to download to learn and to apply.)