Results 201 to 210 of about 1,244,965 (221)
Some of the next articles are maybe not open access.
Endmember extraction analysis considering endmember variability
2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013In recent years, several kinds of endmember extraction algorithms have been proposed from hyperspectral data set which extracts/selects one single standard endmember spectrum for each existing endmember class or scene component. In this article, endmember variability is considered to the mixture spectrum analysis by representing each endmember by a set
Mingming Xu 0001 +2 more
openaire +1 more source
Endmember orthonormal mapping in hyperspectral mixture analysis to address endmember variability
Earth Science Informatics, 2016Spectral unmixing estimates the abundance of each endmember at every pixel of a hyperspectral image. Each material in traditional unmixing algorithms is represented through a constant spectral signature. However, endmember variability always exists due to environmental, atmospheric, and temporal conditions, which leads to poor accuracy of the estimated
Ali Jafari +2 more
openaire +1 more source
IEEE Transactions on Geoscience and Remote Sensing, 2000
Accuracy of vegetation cover fractions, computed with spectral mixture analysis, may be compromised by variation in canopy structure and biochemistry when a single endmember represents top-of-canopy reflectance. In this article, endmember variability is incorporated into mixture analysis by representing each endmember by a set or bundle of spectra ...
C. Ann Bateson +2 more
openaire +1 more source
Accuracy of vegetation cover fractions, computed with spectral mixture analysis, may be compromised by variation in canopy structure and biochemistry when a single endmember represents top-of-canopy reflectance. In this article, endmember variability is incorporated into mixture analysis by representing each endmember by a set or bundle of spectra ...
C. Ann Bateson +2 more
openaire +1 more source
Alternating angle minimization based unmixingwith endmember variability
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016Several techniques exist for dealing with spectral variability in hyperspectral unmixing, such as multiple endmember spectral mixture analysis (MESMA) or compositional models. These algorithms are computationally very involved, and often cannot be executed on problems of reasonable size. In this work, we present a new algorithm for solving the unmixing
Rob Heylen +3 more
openaire +2 more sources
Quantitative assessment of the different methods addressing the endmember variability
2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, 2013Spectral mixture analysis is an important technique to extract desired information from the mixed remotely sensed data. However, current spectral mixture analysis techniques suffered from the endmember variability. Quantitative assessment of SMA techniques with simulated data is critical to understand the influence of endmember variability.
Yuhan Rao +3 more
openaire +1 more source
Classification Using Unmixing Models in Areas With Substantial Endmember Variability
2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2018Q1
Edurne Ibarrola-Ulzurrun +4 more
openaire +4 more sources
A Gaussian mixture model representation of endmember variability for spectral unmixing
2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2016Endmember variability complicates the problem of spectral unmixing. This variability is typically represented by probability distributions or spectral libraries. The present work describes a new distributional representation based on Gaussian Mixture Models (GMMs).
Yuan Zhou 0004 +2 more
openaire +2 more sources
Archetypal analysis for endmember bundle extraction considering spectral variability
2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2018With the development of imaging technology, remote sensing images with a high spatial and spectral resolution have become available and have been used in various applications. Although many endmember extraction algorithms have been proposed for hyperspectral data sets which extract/select the standard endmember spectrum for each existing endmember ...
Mingming Xu 0001 +4 more
openaire +2 more sources
On the effect of variable endmember spectra in the linear mixture model
IEEE Transactions on Geoscience and Remote Sensing, 2006The linear mixture model is frequently used to characterize surface cover over land, to model the reflectance of heterogeneous surfaces, and, by inversion, to estimate fractional cover from a multispectral satellite signal. It is usually assumed that certain parameters of this model, namely the so-called endmember spectra, are fixed, and that the model
openaire +2 more sources
Endmember and band combined model for hyperspectral unmixing with spectral variability
Journal of Applied Remote Sensing, 2020Spectral variability is one of the most limiting factors in hyperspectral unmixing, so it is important to further study the characteristics of spectral variability to improve the accuracy of unmixing. After conducting simulations under varying irradiation conditions, a linear mixed model combining endmember and band is proposed by introducing a band ...
Wuhu Lei +4 more
openaire +1 more source