Snakes

根据离散数据点拟合圆，得到圆心坐标和拟合半径(Fitting the circle according to the discrete data points, the coordinates of the center of the circle and the fitting radius are obtained.)

数字图像非局部均值算法，很好的哦。我自己试过了

Delaunay三角网的逐点插入法. 原始作者 @author Paul Chew * * Created July 2005. Derived from an earlier, messier version.(Delaunay triangulation point by point insertion method. Original author @ author Paul Chew** Created July 2005. Derived from an earlier, messier version.)

OFDM调制的的AWGN加瑞丽衰落信道,其它的我就不多说了(OFDM modulation of AWGN and ruili fading channel, the other I will not say)

三维重建是指对三维物体建立适合计算机表示和处理的数学模型,是在计算机环境下对其进行处理、操作和分析其性质的基础,也是在计算机中建立表达客观世界的虚拟现实的关键技术。(Three-dimensional reconstruction refers to the establishment of a mathematical model suitable for computer representation and processing of three-dimensional objects. It is the basis for processing, manipulating and analyzing their properties in the computer environment. It is also the key technology for establishing a virtual reality to express the objective world in the computer.)

在matlab下用Bilateral filter进行High dynamic range 图像 tune的源代码。读取.hdr文件(可用hrdshop生成)(In matlab under the Bilateral filter used for High dynamic range image of the source code of tune. Read. Hdr file (can be used to generate hrdshop))

利用MATLAB软件编程实现三维重建，对CT图像实现三维体绘制。(CT images of three-dimensional volume rendering reconstruction)

说明：  给定一个图像，其中包含足够的信息来计算地平面消失线和垂直消失点，以及一个已知高度的物体。然后，只要他们的头部和脚都可见，就可以在场景中的任何地方测量站在地平面上的人的高度。(Given an image which contains sufficient information to compute the ground plane vanishing line and the vertical vanishing point, and also one object of known height for which the top and base are imaged. Then the height of a person standing on the ground plane can be measured anywhere in the scene provided that their head and feet are both visible.)

制作人工散斑模拟图，很实用，可直接实用。(Production of artificial speckle simulation maps, very practical, direct and practical.)

低秩的求解 denoise an image by sparsely representing each block with the already overcomplete trained Dictionary, and averaging the represented parts. Detailed description can be found in "Image Denoising Via Sparse and Redundant representations over Learned Dictionaries(low rankdenoise an image by sparsely representing each block with the already overcomplete trained Dictionary, and averaging the represented parts. Detailed description can be found in "Image Denoising Via Sparse and Redundant representations over Learned Dictionaries)