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denseSift.extract dense sift for each image patch
- extract dense sift for each image patch, because no salient keypoint detection and rotation normalization, it is very efficient.,extract dense sift for each image patch, because no salient keypoint detection and rotation normalization, it is very eff
houghForest
- 这个是Dr. Juergan Gall写的检测识别图片中的物体，有关的文章名字是Class-specific Hough Forests for Object detection. hough森林方法结合了随机森林和Hough选票去估计物体中心的可能。-A method for the detection of instances of an object class.A class-specific Hough forest is a random forest that maps image
Stoneage_UpdateTool
- 石器時代補丁更新工具,開私服必備,石器圖像更新工具-Stone Age tools update patch, open私服necessary, update the image of stone tools
correlCorresp
- 寻找相应的特点,在一副图片的基础是许多光流、立体的视觉和图像间的配准算法。一个发现匹配方法简单,取一小块一个图像,计算其滑动互相与其他的形象,并找到一个高峰。此表格提供了课堂的实现方法。-Finding corresponding features in a pair of images is the basis of many optic flow, stereo vision and image registration algorithms. One straightforward app
patch_recon
- 这是基于patch处理的图像处理matlab程序,具有很好的学术研究价值.-This is based on image processing matlab patch treatment program with good academic value.
Sparse Lab 200-Core
- 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-resoluti
CVPR2008
- CVPR2008论文The patch transform and its applications to image editing源代码-CVPR2008 The patch transform and its applications to image editing
Patch-Transform-Application
- 这是MIT一个专门研究图像处理的教授团队做的关于patch transform研究的源代码程序，讲述了其在图像拼接，图像重组方面的应用，工程浩大，但是价值非常高。-This is a MIT professor specializing in image processing team to do research on the patch transform the source code of the program, described in the image mosaic, image
vgg_kdtree2
- kdtree的实现，用来图像检索，检索出与某一副图像中某特征相似度由高到低的n副图像-image patch data stored in k-d trees for fast and discriminatory image patch searches.the implemention of kdtrees
patch-transform-
- 图像处理 图像 缩放 SEAM CARVING PDF-IMAGE PROCESS IMAGE SCALE SEAM CARVING PDF
MR8fast
- 论文《A Statistical Approach to Material Classification Using Image Patch Exemplars》提出的算法C++实现 1）使用了OpenCV2.2.0和VS2010，设置系统环境变量OPENCV_DIR为OpenCV的安装路径，如C:\OpenCV2.2,在path中添加环境变量C:\OpenCV2.2\bin,具体可查看OpenCV的用户手册 2）可zhenjia.dou@gmail.com-The algorithms
image-patch
- 基于matlab的、结合深度图像的图像修补- Image patch based on matlab, combined with the depth of the image
Fusion_old
- A novel higher order singular value decomposition (HOSVD)- based image fusion algorithm is proposed. The key points are given as follows: 1) Since image fusion depends on local information of source images, the proposed algorithm picks out info
Color-image-processing
- 彩色图像处理算法：white patch, gray world, etc.-different algorithms for color image processing
onling_tracker
- 采用在线学习跟踪方式，对物体进行跟踪，代码用c++编写，库用的Opencv库，程序中包括了3个.h，3个.cpp，一个.main程序。-We have added two new state-of-the-art object tracking algorithms to OpenCV which can robustly track images patches across a video sequence and learn online (i.e., on-the-fly) as the
FuzzyCmeansWithWeightedImagePatch
- 对《Fuzzy c-means clustering with weighted image patch for image segmentation》这篇文章进行了实现，运行速度在一分钟之内，希望对研究模糊c均值及其拓展算法的人有所帮助。运行testWIPFCM.m即可，注意改掉文件路径-On " Fuzzy c-means clustering with weighted image patch for image segmentation" This article wa
nlmeans-patch
- 在matlab环境下利用非局部均值滤波对图像处理的SURE估计，很好的程序。-In the matlab environment using nonlocal average filtering SURE estimation for image processing, very good program.
Patch
- 1利用SIFT关键点进行图像匹配 2在视频中，在一帧中检测关键点，之后利用canonical patch传递关键点，经过一定阈值的帧后，再次计算关键点，利用相邻帧之间关键点的差别很小，只更新关键点的位置，提高帧率。 3阈值自动确定-1 uses SIFT image matching key points 2 in the video, detecting critical points in one frame, after which it canonical patch tra
Statistical-Image-Completion-master
- Statistical Image Completion. Image processing project realized for the Image Processing class SI241 at Telecom ParisTech. Based on patches statistics of an image, the program aims at completing a missing part of it. It can be used to delete small ob
Fuzzrinmealenc
- Fuzzy c-means (FCM) clustering has been widely used in image segmentation. However, in spite of its computational efficiency and wide-spread prevalence, the FCM algorithm does not take the spatial information of pixels into consideration, and hence m