-
KNNMeanFilter
说明: 原理:以待处理的像素作为中心,取一个nXn的模板,在模板中选择k个与待处理像素的值最接近的像素,将这k个像素的均值替换原来的像素值。
假设n=3,k=5,调用方法:b = KNNMeanFilter(a, 3, 5)(Principle: to be treated as the center pixel, take a nXn template select the template and the pending k-nearest pixel values of pixels, this k pixels mean replacing the original pixel value. Assuming n = 3, k = 5, call the method: b = KNNMeanFilter (a, 3, 5))
- 2010-05-03 10:14:15下载
- 积分:1
-
meanShiftPixCluster
This is a good demo of showing how the mean shift idea works for image pixel clustering
- 2013-12-17 21:07:04下载
- 积分:1
-
contour_following
matlab 边界跟踪程序,图像要求为二值图像,输出为边界的点的坐标。(matlab boundary tracking procedure, the image requested for the binary image, the output for the coordinates of border points.)
- 2007-07-31 00:02:27下载
- 积分:1
-
Adavance-PID-control
刘金琨先进PID控制MATLAB仿真第二版程序(Liu Jinkun advanced PID control and MATLAB simulation program)
- 2012-08-16 10:45:24下载
- 积分:1
-
BORNE-DU-SHANNON
script shannon limit how to plot it ?
- 2012-11-21 16:51:39下载
- 积分:1
-
张正友摄像机标定
说明: 经典相机标定法,张正友标定法的MATLAB实现,值得借鉴(The classical camera calibration method, zhang zhengyou calibration method MATLAB implementation, it is worth learning)
- 2019-06-22 14:05:47下载
- 积分:1
-
split1
利用分步傅立叶积分法,计算了光纤中色散与SPM效应(Step-by-step use of Fourier integral method, the calculation of the fiber dispersion and SPM.)
- 2011-01-04 10:00:13下载
- 积分:1
-
TX_DTMB2
DTMB,全称Digital Television Terrestrial Multimedia Broadcasting(Digital Television Terrestrial Multimedia Broadcasting)
- 2018-01-18 13:19:07下载
- 积分:1
-
COST207.m
四种典型环境的cost 207模型的matlab仿真信道代码(Four kinds of typical environmental cost 207 model channel matlab simulation code)
- 2008-01-04 09:16:24下载
- 积分:1
-
classical_music_1
MUSIC算法[1]是一种基于矩阵特征空间分解的方法。从几何角度讲,信号处理的观测空间可以分解为信号子空间和噪声子空间,显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成,噪声子空间则由协方差矩阵中所有最小特征值(噪声方差)对应的特征向量组成。(MUSIC algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of view, the signal processing can be decomposed observation space the signal subspace and the noise subspace, it is clear that the two spaces are orthogonal. Signal Subspace data received by the array covariance matrix and eigenvectors corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector components.)
- 2013-09-15 20:25:40下载
- 积分:1