DeepPLearning_book

calibration摄像机镜头的校正程序(calibration Calibration camera lens calibration procedure)

SPIHT的图像压缩算法源代码。可以针对128×128的图像进行压缩(SPIHT image compression algorithm source code. 128 × 128 image compression)

基于dwt的数字图像水印技术的matlab源代码。包括嵌入和提取，效果不错。(Dwt-based digital image watermarking technique matlab source code. Including the embedding and extraction, good results.)

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

非精确ALM解决PCA算法的例子，用后效果不错，发上来分享。(This matlab code implements the inexact augmented Lagrange multiplier method for Robust PCA.)

最大熵图像复原方法，效果还好，这是最近努力的结果，不过或许需要适当的改进之后会有更好的结果，分享一下(Maximum entropy image restoration method, the effect Fortunately, this is the result of recent efforts, but may need to be appropriate to improve after the better results, share)

基于导纳增量法的光伏发电最大功率跟踪算法仿真模型。该模型精度较高，很好的跟踪最大功率点(Based on admittance incremental method of photovoltaic maximum power tracking algorithm simulation model.The model precision, good track the maximum power point)

利用MATLAB实现NSCT非下采样轮廓波变换(Realization of Nonsubsampled Contour Transform by Using MATLAB.)

全变分去噪 J=tv(I,iter,dt,ep,lam,I0) 输入: I - 灰度图像, iter - 迭代次数 [1], dt - 时间步长 [0.2], ep - 提升参数epsilon [1], lam - 保真项 lambda [0], I0 - 输入噪声图像 [I0=I] ([]中的是缺省值)( 全变分去噪 J=tv(I,iter,dt,ep,lam,I0) 输入: I - 灰度图像, iter- 迭代次数 [1], dt - 时间步长 [0.2], ep - 提升参数epsilon [1], lam - 保真项 lambda [0], I0 - 输入噪声图像 [I0=I] ([]中的是缺省值))

MATLAB工具sift实现图像拼接，上下拼接(MATLAB tool sift image stitching, stitching up and down)