Results 131 to 140 of about 763 (175)

Robust endmember extraction in the presence of anomalies

2009 IEEE International Geoscience and Remote Sensing Symposium, 2009
Most available methods for endmember extraction use the convexity of the data structure and consider the vertices of the data as the purest pixels. Such methods do not consider the applicability of the linear mixing model once the endmembers have been extracted. Thus they might return false endmem-bers if the data contain outliers such as anomalies. In
Olga Duran, Maria Petrou
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A new endmember extraction algorithm based on orthogonal bases of subspace formed by endmembers

2007 IEEE International Geoscience and Remote Sensing Symposium, 2007
A new algorithm for decomposition of mixed pixels based on orthogonal bases of data space is proposed in this paper. It extracts endmembers sequentially by adding a new vertex of the simplex with the maximum volume every time. It can avoid the dilemma in traditional simplex-based endmember extraction algorithms such as N-FINDR that it generally ...
Xuetao Tao, Bin Wang 0008, Liming Zhang 0001, Jian Qiu Zhang 0001   +3 more
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A Novel Endmember Bundle Extraction Framework for Capturing Endmember Variability by Dynamic Optimization

IEEE Transactions on Geoscience and Remote Sensing
Cong Lei, Linfu Xie, Xiaoqiong Qin
exaly   +2 more sources

Spatial constraints on endmember extraction and optimization of per-pixel endmember sets for spectral unmixing

2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009
Fractional abundances predicted for a given pixel using spectral mixture analysis (SMA) are most accurate when only the spectral endmembers that comprise it are used, with larger errors occurring if inappropriate endmembers are included in the mixing process.
Benoit Rivard, Derek M. Rogge, Jilu Feng, J. Zhang   +3 more
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An improved full automated endmember extraction algorithm based on endmember independence

SPIE Proceedings, 2015
Current algorithms of endmember extraction generally need to determine the number of endmembers manually. However, the number of endmembers is unknown in practical application, so an automated and iterative endmember extraction algorithm is put forward in this paper to solve the problem.
Yiran Wang, Shengwei Zhong, Ye Zhang
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A Novel Endmember Bundle Extraction and Clustering Approach for Capturing Spectral Variability Within Endmember Classes

IEEE Transactions on Geoscience and Remote Sensing, 2016
Spectral variability, unrelated to the purity of endmembers, can change the geometry of the dataspace and affect conventional methods used to identify endmembers. Several methods have been developed to identify and extract endmember bundles representing the spectral variability within each endmember class.
Tatsumi Uezato, Richard J Murphy, Arman Melkumyan   +2 more
exaly   +2 more sources

Finding Endmember Classes and Endmembers in Hyperspectral Images

2016
Remotely sensed images have been used in a broad range of applications ranging from chemical/biological defense, geology, agriculture to environmental protection, law enforcement and intelligence applications. With the recent advanced technology, remote sensing instruments have significantly improved spatial resolution and also spectral resolution. The
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Endmember Extraction by Exemplar Finder

2013
We propose a novel method called exemplar finder EF for spectral data endmember extraction problem, which is also known as blind unmixing in remote sensing community. Exemplar finder is based on data self reconstruction assuming that the bases endmembers generating the data exist in the given data set.
Yi Guo 0001, Junbin Gao, Yanfeng Sun
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Multiobjective endmember extraction for hyperspectral image

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
Endmember extraction (EE) is one of the most important issues in hyperspectral mixture analysis, and it is also one of the most challenging tasks due to the intrinsic complexity of remote sensing images and the lack of priori knowledge. In recent years, a number of EE methods have been developed, and several different optimization objectives have been ...
Rong Liu, Bo Du 0001, Liangpei Zhang 0001   +2 more
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Associative morphological memories for endmember induction

IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2004
Spectral unmixing of hyperspectral images relies on the knowledge of a set of endmembers, which are usually unknown. One approach is the induction from the image data of the endmember spectra. Endmember spectra correspond to vertices of a convex region that covers the image pixel spectra.
Manuel Graña, Josune Gallego
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