readavi

我做的课题的响应信号，做了响应的小波包能量分析，希望对大家有帮助(I do issue a response signal, so the response of the wavelet packet energy analysis, we want to help)

矫正桶形畸变，只是用了坐标变化，目前在研究张正友的算法，日后会上传的(correct the distortion of picture)

RPCA (Robust Principal Component Analysis)是目前用于矩阵填充、图像去噪的最有效的优化方法。目前最有效的算法是ALM（Augmented Lagrange Multiplier）。ALM分为Exact ALM和Inexact ALM。 该代码是Inexact ALM，收敛速度比Exact ALM快！(RPCA (Robust Principal Component Analysis) is used for matrix filling, image denoising. It is currently the most effective optimization method. Currently the most effective method is ALM (Augmented Lagrange Multiplier). There re 2 kinds of ALM: Exact ALM and Inexact ALM. The code is Inexact ALM, faster convergence speed than the Exact ALM!)

几何变换，包括图形的基本变化，以及计算机图形学中的算法(Geometric transformations, including changes in the basic graphics, and computer graphics algorithms)

图像处理基本操作MATLAB原代码，包括各种经典算法，处理过程源码(Basic operation of image processing the original MATLAB code, including a variety of classic algorithms, process source)

利用MATLAB对图像边界内部的部分进行填充，以便后期对图像处理(Using MATLAB within the boundaries of the part of the image to fill, so that the latter part of the image processing)

对lagrange函数公式进行代码化，可以对一组数进行插值算法，可以输出最后的y值(The lagrange function formula code, a number of groups interpolation algorithm, you can output the final value of y)

阴影消除matlab代码，运行可用，可供参考(The shadow eliminates the matlab code, which is available for reference)

说明：  基于log Gabor小波的相位一致图像纹理特征分析(Based on log Gabor wavelet phase consistent image texture analysis)

说明：  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。 该方法于 1999 年由 David Lowe 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。(来自百度)(SIFT, namely Scale-invariant feature transform (SIFT), is a description used in the field of image processing. This description has scale invariance and can detect key points in images. It is a local feature descriptor. This method was first published by David Lowe at the International Conference on Computer Vision (ICCV) in 1999 and published in the International Journal of Computer Vision (IJCV) in 2004 after it was sorted out and perfected by David Lowe again. As of August 2014, more than 25,000 citations have been cited. (From Baidu))