搜索资源列表
compairusgs
- 实现解混光谱与光谱库里对应光谱的比对,可以找到光谱库里与其最相近的光谱,可以进行直观的评价-Spectroscopy and Spectral unmixing achieve Curry corresponding spectra comparison, you can find their closest spectral library spectra can be visually evaluated
demo_sparse_tv
- 基于全变分空间正则化的稀疏超普解混算法的MATLAB程序-Matlab programs for “Total variation spatial regularization for sparse hyperspectral unmixing”
colaborative-demo
- 基于协同稀疏表示的解混方法,因为每个端元的相似性,本文采用协同稀疏表示来约束每个像素采用相同位置系数不同的原子-Collaborative Sparse Regression for Hyperspectral Unmixing
ICA-matlab
- ICA算法的研究可分为基于信息论准则的迭代估计方法和基于统计学的代数方法两大类,从原理上来说,它们都是利用了源信号的独立性和非高斯性。一般情况下,所获得的数据都具有相关性,所以通常都要求对数据进行初步的白化或球化处理,因为白化处理可去除各观测信号之间的相关性,从而简化了后续独立分量的提取过程,然后再用基于负熵最大的FastICA算法,即可对图像及信号进行解混。-ICA algorithm research can be divided into iterative estimation meth
NMF-matlab
- nmf即是非负矩阵分解,就是把一个非负的源矩阵分解为两个非负的矩阵,在光谱解混中用的较多。-nmf that is non-negative matrix factorization, it is the source of a non-negative matrix factorization of two non-negative matrix, more mixed with the solution in the spectrum.
vca
- 顶点成分分析,用于光谱影像的端元提取,是混合像元解混的一个步骤-Vertex component analysis code
unmixing_overview
- 关于高光谱解混的代码 来源于hyperspectral unmixing 详细的说明可以见内部说明文件-Hyperspectral Solutions of mixed code hyperspectral unmixing can see a detailed descr iption of internal documentation
unmixed
- 用于遥感中的高光谱数据,实现无约束、合为1约束或非负约束条件下的端元解混-use for unmixing in hyperspectral remote sensing
RSFoBa-Demo
- 一种效果比较好的高光谱解混算法,模拟数据以及真实数据的实验都在,直接可以跑。-An effect good hyperspectral unmixing algorithm, experimental simulation data and real data are in, you can directly run.
FastICA
- 快速独立成分分析算法,尤其适用于脑电信号解混。-Fast ICA
KurtNoiseDelete
- 利用峭度的特性删除进过解混后的噪声信道,更适用于脑电信号的处理。-Using characteristic of kurtosis to delete nongaussianity noise.
MLNMF_Demo
- matlab——多层非负矩阵分解光谱解混代码-Spectral Unmixing of Hyperspectral Imagery Using Multilayer NMF
实验6_NMF-ICA
- 实现非负矩阵分解算法和独立成分分析,得到遥感遥感图像解混结果(The non negative matrix factorization algorithm and independent component analysis are implemented to get the unmixing results of remote sensing images)
EASI
- 盲源分离中的EASI算法,程序中提供源信号(源信号均为次高斯信号),固定的信道混合矩阵,EASI分离算法。EASI算法为定步长EASI算法,步长固定。程序中包含PI值收敛曲线程序。整体程序可以产生源信号图、混合信号图、解混信号图、PI值收敛曲线。(The EASI algorithm in the blind source separation provides the source signal (the source signal is the next Gaussian signal),
7941943ICA
- 独立分量分析代码,ICA的目的就是寻找解混矩阵W(A的逆矩阵),然后对X进行线性变换,得到输出向量U(Independent Component Correlation Algorithm)
BSA PPN
- 基于PPNMM使用一种新的搜索目标算法CS算法,来实现对图像解混(Based on PPNMM, a new search target algorithm CS algorithm is used to realize image mixing.)
PCA
- 2种主成分分析方法,高光谱降维,基于实测光谱数据,光谱解混(endmember extraction matlab)
CFICA_11
- ICA的目的就是寻找解混矩阵W(A的逆矩阵),然后对X进行线性变换,得到输出向量U。(The purpose of ICA is to find the mixed matrix W (the inverse matrix of A), and then the linear transformation of the X, and the output vector U is obtained.)
FastICA25
- 独立主成分分析目的就是寻找解混矩阵W(A的逆矩阵),然后对X进行线性变换,得到输出向量U。(Independent Component Correlation Algorithm)
DemoMVSA
- 一种快速的高光谱解混算法,采用单形体体积最小为准则(A fast hyper spectral mixing method.Using the minimum volume of a single form as the criterion.)