Image Feature Extraction of Code

基于块匹配的稳像算法，包括演示视频，非常全面，希望对大家有帮助(Stabilization based on block matching algorithms, including a demonstration video, very comprehensive, we hope to help)

基于PCL的估算散乱点云的法矢量，并进行颜色渲染显示(estimation of normal vectors for point clouds and color rendering display based on PCL)

混合高斯分布EM算法，可以算混合高斯分布的三个参数。混合高斯分布更接近系数分布。(mixed Gaussian distribution EM algorithm can calculate mixed Gaussian distribution of the three parameters. Mixed closer to the Gaussian distribution coefficient.)

vc编写数字图像处理的程序,其中有图像处理的各种方法的程序(Vc write a digital image processing program, including the various methods of image processing program)

说明：  本压缩包主要包括数字图像处理——使用MATLAB分析与实现的源代码(This compression package mainly includes digital image processing - using MATLAB analysis and implementation of the source code)

传统的HSV空间颜色特征提取算法，量化为8H3S3V.(HSV color space for the traditional feature extraction algorithm, to quantify 8H3S3V.)

医学图像配准，医学图像2D_3D配准，基于vc++开发。(The registration of pre-operative volumetric datasets to intra-operative two-dimensional images provides an im- provedway of verifying patient positionandmedical instru- ment location. In applications from orthopedics to neuro- surgery, it has a great value in maintaining up-to-date in- formation about changes due to intervention. We propose a mutual information-based registration algorithm which es- tablishes the proper alignment via a stochastic gradient as- centstrategy. Ourmaincontributionliesinestimatingprob- ability density measures of image intensities with a sparse histogrammingmethodwhichcouldlead to potentialspeed- up over existing registration procedures and deriving the gradient estimates required by the maximization procedure. Experimental results are presented on fluoroscopy and CT datasets of a real skull, and on a CT-derived dataset of a real skull, a plastic skull and a plastic lumbar spine seg- ment.)

DIC测试，适用于二维数字图像相关法，采用的ZNSSD，输入图像需为灰度图像，输出仿射矩阵(Measuring strain in samples which are too small, big, compliant, soft or hot are typical scenarios where non-contact techniques are needed. A technique which can cover all that and also can deal with complicated strain fields in structures or structural materials is the Digital Image Correlation. With this technique, strain can be calculated from a series of consecutive images with sub pixel resolution as will be shown in the following chapters.)

该软件可实现图像间格式的转换,主要实现: (e)ps,bmp, jpg, png,tif,gif, psdi图像格式之间的转换(The software enables format conversion between images, the main achievement: (e) ps, bmp, jpg, png, tif, gif, psdi image format conversion between)

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)