united1

利用K均值聚类的方法实现人体的检测，混合高斯模型建立背景并实时更新(The use of K-means clustering method to achieve the human body detection, Gaussian mixture model to establish the background and real-time updates)

一个快速而精确的一阶稀疏图像复原算法。主要应用于图像去噪声。(A fast and accurate first-order sparse image restoration algorithm. Is mainly used in the image to the noise.)

说明：  Matlab曲波变换工具箱，安装在matlab上，可以应用曲波变换(Matlab curvelet transformation toolbox)

用代数迭代算法ART重建图像，含MATLAB代码(image reconstruction using ART algorithms (MATLAB code))

Log整合功能. 自動整理紀錄檔部份檔案.(Log Arrange. Auto Message.)

Stereoscopic video coding

带高斯白噪声的Kalman滤波Matlab代码，每一步都有详细的注释，和kalman滤波的五个公式对应。并有高斯白噪声的产生函数，function G = CreateGauss(E,D,M,N) 产生均值为E,方差为D,MxN的高斯白噪声矩阵(The Matlab code of Kalman filter with Gaussian white noise.)

通过一阶重建方法实现总变差的图像算法源码，希望对学习超分辨率的朋友有所帮助。 (Algorithms and software for total variation image reconstruction via first-order methods)

SIFT，即尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点，是一种局部特征描述子。[1] 该方法于1999年由David Lowe[2] 首先发表于计算机视觉国际会议（International Conference on Computer Vision，ICCV），2004年再次经David Lowe整理完善后发表于International journal of computer vision（IJCV）。截止2014年8月，该论文单篇被引次数达25000余次。(SIFT, namely Scale Invariant Feature Transform (Scale-invariant feature transform, SIFT), it is a description for image processing. This description has scale invariance, can detect critical point in the image, it is a local feature descriptor. [1] The method in 1999 by David Lowe [2] First published in the International Conference on Computer Vision (International Conference on Computer Vision, ICCV), 2004 was again perfect finishing after David Lowe published in the International journal of computer vision (IJCV) . As of August 2014, the paper cited the number of times a single article of more than 25,000 times.)

这是针对波前编码成像系统模拟，以及图像复原模拟代码(this is the wavefront coding image processing code of WFC optic system. it is very useful in WFC syetem for research .)