Results 171 to 180 of about 835 (219)

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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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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Towards streaming hyperspectral endmember extraction

2011 IEEE International Geoscience and Remote Sensing Symposium, 2011
A prevalent methodology for extracting pure pixels from hyperspectral images has been the use of linear-mixture geometry, which dictates that pure components must reside at the corners of a simplex enclosing all the remaining points (the mixtures). Recently, adaptations to popular algorithms for estimating the largest simplex (e.g.
Dzevdet Burazerovic, Rob Heylen, Paul Scheunders   +2 more
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Improved sequential endmember extraction algorithms

2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2011
Most of sequential endmember extraction algorithms, such as iterative error analysis (IEA), vertex component analysis (VCA), and simplex growing algorithm (SGA), use sequential forward selection (SFS) searching strategy. The advantage is its low computational complexity. However, it is sensitive to the initial condition. To reduce the “nesting effect”,
Qian Du 0001, He Yang, Nicolas H. Younan
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Real-Time Endmember Extraction on Multicore Processors

IEEE Geoscience and Remote Sensing Letters, 2011
In this letter, we discuss the use of multicore processors in the acceleration of endmember extraction algorithms for hyperspectral image unmixing. Specifically, we develop computationally efficient versions of two popular fully automatic endmember extraction algorithms: orthogonal subspace projection and N-FINDR. Our experimental results, based on the
Alfredo Remón, Sergio Sánchez, Abel Paz, Enrique S. Quintana-Ortí, Antonio Plaza   +4 more
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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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Automatic algorithms for endmember extraction

SPIE Proceedings, 2006
Endmenber extraction has received increasing interests in hyperspectral image analysis. Two major issues are of interest. One is determination of endmembers, p, required to be generated and the other is generation of initial endmembers. Since most endmember extraction algorithms (EEAs) use randomly generated vectors as their initial endmembers to ...
Chao-Cheng Wu, Chein-I Chang
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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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Multi-objective endmember extraction for hyperspectral images

2017 IEEE Congress on Evolutionary Computation (CEC), 2017
Endmember extraction is a critical step of spectral unmixing. In this paper, a novel endmember extraction algorithm based on evolutionary multi-objective optimization is proposed for hyperspectral remote sensing images. In the proposed method, endmember extraction is modeled as a multi-objective optimization problem.
Hao Li 0009, Jingjing Ma 0001, Jia Liu 0020, Maoguo Gong, Mingyang Zhang 0002   +4 more
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Endmember Extraction Methods: A Short Review

2008
The analysis of hyperspectral images on the basis of the spectral decomposition of their pixels through the so called spectral unmixing process, has applications in thematic map generation, target detection and unsupervised image segmentation. The critical step is the determination of the endmembers used as the references for the unmixing process.
Miguel Angel Veganzones, Manuel Graña
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