fourier

图像的超分辨率重建，比利用了三次插值好，matlab代码，初学者(Image super-resolution reconstruction, than the use of three interpolation is good, matlab code, beginners)

精通MATLAB图像处理第2章所有的程序代码或实例代码(Proficient in MATLAB image processing Chapter 2 program code or code examples)

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)

模式识别中运用ICA进行特征提取的matlab代码(Pattern Recognition in the use of ICA for feature extraction matlab code)

实现直角坐标系至极坐标系下的图形图像变换。本方法为最新的快速变换方法，可应用于相位相关下的带旋转平移、缩放等变换。(the method can transform pic to radan.it can be used by PC to get the roation.)

说明：  小波模极大值用于边缘特征提取.很好的一个matlab算法，可以直接验证。(Wavelet modulus maxima for edge feature extraction algorithm matlab good one can be directly verified.)

说明：  SURF的实现代码,用于图像特征提取，对于入门计算机视觉的同学有帮助(SURF implementation code for image feature extraction, for beginners of computer vision students help)

对Lena图先进行jpeg压缩，再对压缩后的图像分别进行小波软阈值去噪和非抽样硬阈值去噪，比较两种去噪方案，非抽样硬阈值有更好的效果。这是根据一篇外文文献来进行编程的，最后有图像对比结果。(According to the paper of OPTIMAL WAVELET THRESHOLDING FOR VARIOUS CODING SCHEMES ,I firstly compresse the Lena picture using the jpeg method ,then respectivly denoise it using the wavelet soft-thresholding method and the undecimated DWT hard-thresholding method.Comparing the two method ,we can find the undecimated DWT hard-thresholding have a better result.)

说明：  采用 MATLAB 开发环 境，提出了一种图像信息隐藏算法，实现了图像信息隐藏的两大基本功能，即信息的嵌入和信息的提取．同 时，模拟常见的攻击方法，验证了添加隐藏信息后的图像的抗攻击能力(Using MATLAB to develop the environment, an image information hiding algorithm is proposed, which realizes two basic functions of image information hiding, i.e. information embedding and information extraction. At the same time, common attack methods are simulated to verify the anti-attack capability of the image added with hidden informati)

The tool box contains the matlab code for image denosing in nsct.