gaosilvbo

基于自适应的区域选择和自适应的正则化得图像去模糊和超分辨处理，试过可以用(Based adaptive region selection and adaptive regularization was image deblurring and super-resolution processing)

混合高斯模型提取视频帧前景背景图像，经试验验证准确率比较高(Mixed gaussian model to extract video frame prospects background image)

图像增强里的小程序，有中值滤波，平滑处理还有频域增强(Image Enhancement in the small procedures, median filtering, smoothing also enhanced the frequency domain)

surf特征点提取与匹配，该算法能达到实时性的要求，不仅能用于两幅图的匹配，还能用于单幅图的复制粘贴取证(surf feature point extraction and matching, this algorithm can achieve real-time requirements, not only for the two graph matching, but also for single figure copy and paste forensics)

区域图象分割的源码，基于区域增长的分割的代码(Image segmentation of the source region, regional growth based on code division)

LTE中速率匹配的代码，包括子块交织，比特搜集，比特选择和修剪(The code rate matching in LTE, including the sub-block interleaving and bit gather, bit selection and pruning)

说明：  基于开源计算机视觉库OpenCV的图像处理基于开源计算机视觉库OpenCV的图像处理(Based on open source computer vision library OpenCV image processing based on open source computer vision library OpenCV image processing)

说明：  数字图像处理：阈值分割及形态学处理，本程序出色的完成了图形提取，内容包括程序，讲解和运行结果(Digital image processing: segmentation and morphology threshold treatment, the procedure was completed excellent graphics extraction, including procedures and operations on the results of)

斯坦福大学的姚邦鹏开发的一个图像分类算法，使用random forest实现了图像的精细区域描述，赢得了PASCAL VOC2011图像分类竞赛中的winner prize.经测试，程序完全可运行，且提供了MAC和Windows下的两种程序。(Image Classification: An Integration of Randomization and Discrimination in A Dense Feature Representation The goal of our method is to identify the discriminative fine-grained image region that distinguishes different classes. To achieve this goal we sample image regions from dense sampling space and use a random forest algorithm with discriminative classifier. Each node of the tree of random forest is trained and tested with fine-grained image patches combining the information from upstream nodes together. We implemented each node of the tree with a discriminative SVM classifier, which makes the node as a strong classifier. )

三维labeling_GM_PHD程序,三维labeling_GM_PHD程序(The dimensional labeling_GM_PHD procedures,matlab programme!The dimensional labeling_GM_PHD procedures,matlab programme!)