Hyperspectral unmixing (HU) is an important task for remotely sensed hyperspectral (HS) data exploitation. It comprises the identification of pure spectral signatures (endmembers) and their corresponding fractional abundances in each pixel of the HS data cube. Several methods have been developed for (semi-) supervised and automatic identification of endmembers and abundances. Recently, the statistical dual-depth sparse probabilistic latent semantic analysis (DEpLSA) method has been developed to tackle the HU problem as a latent topic-based approach in which both endmembers and abundances can be simultaneously estimated according to the semantics encapsulated by the latent topic space. However, statistical models usually lead to computationa...
Remote hyperspectral sensors collect large amounts of data per flight usually with low spatial resol...
The storage and processing of remotely sensed hyperspectral images (HSIs) is facing important challe...
Hyperspectral imaging can be used for object detection and for discriminating between different obje...
Hyperspectral unmixing (HU) is an important task for remotely sensed hyperspectral (HS) data exploit...
This paper presents a novel approach for spectral unmixing of remotely sensed hyperspectral data. It...
Hyperspectral images are used in different applications in Earth and space science, and many of thes...
Hyperspectral imaging has become one of the main topics in remote sensing applications, which compri...
This letter presents a new parallel method for hyperspectral unmixing composed by the efficient comb...
Hyperspectral data compression and dimensionality reduction has received considerable interest in re...
Many Hyperspectral imagery applications require a response in real time or near-real time. To meet t...
One of the main problems of hyperspectral data analysis is the presence of mixed pixels due to the l...
Effective classification algorithm is a key to extracting interesting and useful information from hy...
Abstract—Spectral unmixing is an important technique for hyperspectral data exploitation. It amounts...
Abstract—Spatial/spectral algorithms have been shown in pre-vious work to be a promising approach to...
A popular algorithm for hyperspectral image interpretation is the automatic target generation proces...
Remote hyperspectral sensors collect large amounts of data per flight usually with low spatial resol...
The storage and processing of remotely sensed hyperspectral images (HSIs) is facing important challe...
Hyperspectral imaging can be used for object detection and for discriminating between different obje...
Hyperspectral unmixing (HU) is an important task for remotely sensed hyperspectral (HS) data exploit...
This paper presents a novel approach for spectral unmixing of remotely sensed hyperspectral data. It...
Hyperspectral images are used in different applications in Earth and space science, and many of thes...
Hyperspectral imaging has become one of the main topics in remote sensing applications, which compri...
This letter presents a new parallel method for hyperspectral unmixing composed by the efficient comb...
Hyperspectral data compression and dimensionality reduction has received considerable interest in re...
Many Hyperspectral imagery applications require a response in real time or near-real time. To meet t...
One of the main problems of hyperspectral data analysis is the presence of mixed pixels due to the l...
Effective classification algorithm is a key to extracting interesting and useful information from hy...
Abstract—Spectral unmixing is an important technique for hyperspectral data exploitation. It amounts...
Abstract—Spatial/spectral algorithms have been shown in pre-vious work to be a promising approach to...
A popular algorithm for hyperspectral image interpretation is the automatic target generation proces...
Remote hyperspectral sensors collect large amounts of data per flight usually with low spatial resol...
The storage and processing of remotely sensed hyperspectral images (HSIs) is facing important challe...
Hyperspectral imaging can be used for object detection and for discriminating between different obje...