fusion

说明：  本代码总结了信息熵、条件信息熵、PSNR、SSIM等图像评价指标(This code summarizes information entropy, conditional information entropy, PSNR, SSIM and other image evaluation indexes)

混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)

说明：  通过matlab，可以快速得到图像的信噪比，峰值信噪比等。里面也有一些解释(Through MATLAB, the signal-to-noise ratio and peak signal-to-noise ratio of image can be obtained quickly. There are also some explanations)

otsu s multilevel thresholding method

基于C++MFC平台进行NDVI计算、最小距离分类、K均值分类，BP神经网络分类等以及精度评价(Based on C++MFC platform, NDVI computing, minimum distance classification, K mean classification, BP neural network classification and accuracy evaluation are carried out.)

灰度共生矩阵 图像纹理特征提取 matlab语言编写(GLCM texture feature extraction matlab language)

仿真一篇国际学会论文。主要是分割粘连细胞图像。(Simulation of an International Society papers. Mainly adhesion cell image segmentation.)

sift算法在cv领域的重要性不言而喻，该作者的文章引用率在cv界是number1.本篇博客只是本人把sift算法知识点整理了下，以免忘记。本文比较早的一篇博文opencv源码解析之(3)：特征点检查前言1 中有使用opencv自带的sift做了个简单的实验，而这次主要是利用Rob Hess的sift源码来做实验，其实现在的opencv版本中带的sift算法也是Rob Hess的，只是稍微包装了下。 下面来做下试验,试验sift代码采用Rob Hess的代码，opencv目前版本中的sift源码也是采用Rob Hess的。代码可以在他的主页上下载：http://blogs.oregonstate.edu/hess/code/sift/ 这里我下载的是windows版本的，并采用Qt做了个简单的界面。(sift algorithm is self-evident the importance of the cv field, the author of the article referenced in the cv sector is number1 this blog I just sift algorithm knowledge compiled under, so as not to forget. This article compares the earlier blog post opencv source code analysis (3): check the preface of the feature points 1 the opencv bring their own sift to do a simple experiment, but this time Rob Hess' s sift source to experiment. In fact, with the opencv version sift algorithm is Rob Hess, only slightly packing the next. Below to do the next test, test sift code using the code of Rob Hess, sift source opencv version of Rob Hess. The code can be downloaded on his home page: http://blogs.oregonstate.edu/hess/code/sift/ here I downloaded the windows version, and using Qt to do a simple interface.)

利用gabor滤波器方法提取视网膜血管，在提取之前进行预处理。gabor滤波器参数选择的是3个角度，12个方向(Gabor filter method is utilized to extract the retinal blood vessels, preprocessing before extraction. Gabor filter parameter selection are three angles, 12 direction )

软阈值去噪加中值滤波，m文件，直接运行，有gui界面(Plus soft thresholding median filter, m files, directly run a gui interface)