Results 41 to 50 of about 265 (159)
IET Image Processing, Volume 16, Issue 13, Page 3557-3566, 13 November 2022., 2022 Abstract Although hyperspectral data, especially spaceborne images, are rich in spectral information, their spatial resolution is usually low due to the limitation of sensor design and other factors. Therefore, for the application of hyperspectral images, unmixing technology is a key processing technology, such as linear mixing model and its derived ...
Haoyang Yu +5 more
wiley +1 more source
Nonlinear unmixing of hyperspectral images using a generalized bilinear model [PDF]
, 2011 Nonlinear models have recently shown interesting properties for spectral unmixing. This paper studies a generalized bilinear model and a hierarchical Bayesian algorithm for unmixing hyperspectral images. The proposed model is a generalization not only of
Altmann, Yoann +9 more
core +1 more source
Comparative Analysis of Automated Text Summarization Techniques: The Case of Ethiopian Languages
Wireless Communications and Mobile Computing, Volume 2022, Issue 1, 2022., 2022 Nowadays, there is an abundance of information available from both online and offline sources. For a single topic, we can get more than hundreds of sources containing a wealth of information. The ability to extract or generate a summary of popular content allows users to quickly search for content and obtain preliminary data in the shortest amount of ...
Wubetu Barud Demilie, Danfeng Hong
wiley +1 more source
Residual component analysis of hyperspectral images - Application to joint nonlinear unmixing and nonlinearity detection [PDF]
, 2014 This paper presents a nonlinear mixing model for joint hyperspectral image unmixing and nonlinearity detection. The proposed model assumes that the pixel reflectances are linear combinations of known pure spectral components corrupted by an additional ...
Altmann, Yoann +10 more
core +1 more source
Nonlinearity detection in hyperspectral images using a polynomial post-nonlinear mixing model [PDF]
, 2012 This paper studies a nonlinear mixing model for hyperspectral image unmixing and nonlinearity detection. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian
Altmann, Yoann +3 more
core +1 more source
Deep Half-Siamese Networks for Hyperspectral Unmixing
, 2021 International audienceOver the past decades, numerous methods have been proposed to solve the linear or nonlinear mixing problems in hyperspectral unmixing (HU).
Hong, Danfeng +4 more
core +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Hyperspectral unmixing (HU) has become an important technique in exploiting hyperspectral data since it decomposes a mixed pixel into a collection of endmembers weighted by fractional abundances.
E. M. M. B. Ekanayake +7 more
doaj +1 more source
Multimodal Hyperspectral Unmixing: Insights From Attention Networks
, 2022 International audienceDeep learning (DL) has aroused wide attention in hyperspectral unmixing (HU) owing to its powerful feature representation ability.
Hong, Danfeng +5 more
core +1 more source
Deep convolutional transformer network for hyperspectral unmixing
European Journal of Remote Sensing, 2023 Hyperspectral unmixing (HU) is considered one of the most important ways to improve hyperspectral image analysis. HU aims to break down the mixed pixel into a set of spectral signatures, often commonly referred to as endmembers, and determine the ...
Fazal Hadi +3 more
doaj +1 more source
Illumination invariance and shadow compensation via spectro-polarimetry technique [PDF]
, 2013 A major problem for obtaining target reflectance via hyperspectral imaging systems is the presence of illumination and shadow effects. These factors are common artefacts, especially when dealing with a hyperspectral imaging system that has sensors in the
Jackman, James +6 more
core +1 more source