BilateralFiltering

Keren 配准的MATLAB源程序，可以进行图像配准及超分辨率运算(Keren registration of the MATLAB source code)

数字图像处理中常用的标准图像，包括大家所共知的lena等图片的高分辨率版本，推荐大家下载(Commonly used in digital image processing standard images, including all the known to the lena and other high-resolution version of the picture, we recommend downloading)

包含二维曲波变换、反变换；三维曲波变换；二维曲波变换(Including two-dimensional Qu Bo transform, inverse transform, 3D Qu Bo transform, and two-dimensional Qu Bo transform)

用C语言实现位图格式的图像读取功能，可直接使用。(read BMP by C ,can be used directly.)

描述OFDM高峰均功率比（PAPR)的CCDF曲线，用MATLAB仿真的结果(Description OFDM peak-average power ratio (PAPR) of the CCDF curve, the results of simulation using MATLAB)

document about computer vision - image processing

小波变换实现图像增强的示例，matlab编写。(an example of image enhacement based on wavelet transformation, writed by matlab.)

说明：  bp神经网络在图像压缩中的应用源代码，欢迎下载。(bp neural network in image compression source code, welcome to download.)

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)

通论算法，给人脸做重构处理，进一步完成人脸的样本稀疏化，还能更好的重构人脸。(The General Theory of algorithms, giving face to do reconstruction processing to complete further thinning of face samples, but also to better reconstruct the face.)