matblab笔记2

基于最小二乘法的相位解缠VC++算法 (least squares method based on the VC Phase Unwrapping Algorithms)

gabor小波变换提取图像纹理信息，得到一维向量。(gabor wavelet transform to extract image texture information)

通过使用块匹配法实现运动矢量的检测，块大小和搜索区域大小可自定(Achieved through the use of block matching motion vector detection, block size and search area size can be customized)

1、读取显示所给PET图像（SE2IM210）。 2、学习imhist函数，画出所给PET图像的直方图。 3、根据直方图为该PET图像选择合适的显示窗（imshow参数），使胸 部轮廓等解剖结构可见。 4、根据直方图选择合适阈值，分割肿瘤区域与正常区域，计算肿瘤区 域内图像灰度均值、方差、最大值及最小值。(1 give PET images displayed, read (SE2 IM210). 2, learning, imhist function, draw the give PET image histogram. 3, according to the histogram for the PET image to choose the appropriate display window (imshow parameters), make bosom Outline of anatomical structures such as visible. 4, according to the histogram, choose appropriate threshold segmentation tumor area and normal area, calculating the tumor area In the domain of image grayscale average and variance, the maximum and minimum values.)

主成分分析方法（PCA），PCA算法的理论依据是K-L变换，通过一定的性能目标来寻找线性变换W，实现对高维数据的降维。(Principal component analysis (PCA), PCA algorithm is based on the theory of KL transform, through a certain performance targets to find the linear transformation W, the realization of high-dimensional data, dimensionality reduction.)

利用维纳滤波实现噪声中的语音信号恢复，产生chirp信号，噪声为高斯白噪声，噪声叠加在chirp信号上，构成观测信号x(n),使用编程方法实现使用维纳滤波滤除高斯噪声。(Wiener filtering the voice signal recovery in the noise generated chirp signal, the noise is Gaussian white noise, noise superimposed on the chirp signal, constitute the observed signal x (n), using the programming method using the Wiener filter filter Gaussian noise.)

用matlab实现levelset水平集分割图像！(levelset to fen ge Image ag dag gf a ga ga h agr d we v g)

图像读取与显示，图像二值化，边缘检测，边缘追踪(Read and display image, image binarization, edge detection, edge tracking)

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.)

一种快速图像阈值分割法，不是otsu或迭代法，Wellner 1993快速自适应的图像二值化方法，有具体使用方法，很详细(A fast image thresholding segmentation method, not otsu or iterative methods, Wellner 1993 fast adaptive image binarization method)