Mixed pixel separation has always been a hotspot issue of quantitative remote sensing and is especially important for hyperspectral imagery. A new method based on independent component analysis is proposed in this paper to blind separate component information including the signature and the weight from the spectrum of mixed pixels. The extra information is obtained from the statistical characters of the signatures. To evaluate the performance of the algorithm some computer numerical simulations are conducted and a method to choose a best band coverage of the spectrum using for blind signal separation is proposed. Finally the algorithm is applied on the HYPERION imagery of Henshan, Shanxi Provience and the result showed that the method is ef...
In this paper, an ICA-based approach is proposed for hyperspectral image analysis. It can be viewed ...
One of the most challenging task underlying many hyperspectral imagery applications is the spectral ...
The paper presents an algorithm based on Independent Component Analysis (ICA) for the detection of s...
Mixed pixel separation has always been a hotspot issue of quantitative remote sensing and is especia...
Blind signal separation (BSS) based on the technique of independent component analysis (ICA) was int...
This paper describes a new algorithm for feature extraction on hyperspectral images based on blind s...
This paper describes a new algorithm for feature extraction in hyperspectral images based on Indepen...
The paper presents a novel algorithm based on Independent Component Analysis (ICA) for the detection...
This paper introduces a new method to blindly unmix hyperspectral data, termed dependent component a...
Independent component analysis (ICA) is a very popular method that has shown success in blind source...
In land investigation, it is often required to extract plant and vegetation information from land co...
This paper introduces a new hyperspectral unmixing method called Dependent Component Analysis (DECA)...
This paper investigates the effect of spectral screening on processing hyperspectral data through In...
The study adresses the problem of spectral unmixing hyperspectral images, technique allowing the spe...
The goal of this dissertation is to investigate the applicability of Independent Component Analysis ...
In this paper, an ICA-based approach is proposed for hyperspectral image analysis. It can be viewed ...
One of the most challenging task underlying many hyperspectral imagery applications is the spectral ...
The paper presents an algorithm based on Independent Component Analysis (ICA) for the detection of s...
Mixed pixel separation has always been a hotspot issue of quantitative remote sensing and is especia...
Blind signal separation (BSS) based on the technique of independent component analysis (ICA) was int...
This paper describes a new algorithm for feature extraction on hyperspectral images based on blind s...
This paper describes a new algorithm for feature extraction in hyperspectral images based on Indepen...
The paper presents a novel algorithm based on Independent Component Analysis (ICA) for the detection...
This paper introduces a new method to blindly unmix hyperspectral data, termed dependent component a...
Independent component analysis (ICA) is a very popular method that has shown success in blind source...
In land investigation, it is often required to extract plant and vegetation information from land co...
This paper introduces a new hyperspectral unmixing method called Dependent Component Analysis (DECA)...
This paper investigates the effect of spectral screening on processing hyperspectral data through In...
The study adresses the problem of spectral unmixing hyperspectral images, technique allowing the spe...
The goal of this dissertation is to investigate the applicability of Independent Component Analysis ...
In this paper, an ICA-based approach is proposed for hyperspectral image analysis. It can be viewed ...
One of the most challenging task underlying many hyperspectral imagery applications is the spectral ...
The paper presents an algorithm based on Independent Component Analysis (ICA) for the detection of s...