搜索资源列表
VariableWeightMRMRF
- 基于变权重MRF的图像分割算法，特征场是使用混合高斯模型，标记场使用Pott模型，基于迭代条件模式进行分割-MRF based on weighted image segmentation algorithm, feature field is the use of Gaussian mixture model, using the tag field Pott model segmentation based on iterative model conditions
iteration_algorithm
- 高斯白噪声模型下的一种图像分割的迭代算法-Gaussian white noise model of a iterative algorithm for image segmentation
TVdenoising-
- 全变差图像去噪，用的分裂Bregman迭代算法，分别用到了L1,、L2、和Lp范数来做的，其中在L1模型中还用到了高斯赛德尔迭代和收缩算子，-Total variation image denoising, with split Bregman iterative algorithm, respectively, used in the L1,, L2, and Lp norm to do, which is also used in the L1 model iterations and hi
Iterative-Fourier-algorithm-(GS)
- 迭代傅里叶算法实现对高斯光束的整形：用malab将二维的高斯分布图形转化成三维的分布的方法和用迭代傅里叶变换（GS）的算法对高斯光束的整形做对比-Iterative Fourier algorithm of gaussian beam shaping: the two-dimensional gaussian distribution with malab graphics into three-dimensional distribution method and using iterativ
EM
- EM算法，迭代得到高斯混合模型对原数据进行估计.直接运行EM.m，可以直观观察运行结果-use EM algorithm to get GMM(Gaussion Mixture Model)
EmGMM
- 高斯混合模型的最大期望迭代求解算法,可用于图像区域灰度分布估计-Expectation maximazation(EM) for Gaussian mixture model(GMM)
58796044
- 雅克比迭代,求解方程近似解 秦九昭算法 幂法 高斯塞德尔()