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A New Sequential Algorithm for Hyperspectral Endmember Extraction [PDF]
IEEE Geoscience and Remote Sensing Letters, 2012 Endmember extraction is an important step in spectral mixture analysis when endmembers are unknown. Endmembers are usually assumed to be pure pixels present in an image scene. Under this circumstance, endmember extraction is to find the most distinctive pixels.
Qian Du
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Multiobjective endmember extraction for hyperspectral image
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017Endmember 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 +2 more
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Towards streaming hyperspectral endmember extraction
2011 IEEE International Geoscience and Remote Sensing Symposium, 2011A 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 +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), 2011Most 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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Automatic algorithms for endmember extraction
SPIE Proceedings, 2006Endmenber 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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Endmember Extraction Methods: A Short Review
2008The 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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A new endmember extraction algorithm based on orthogonal bases of subspace formed by endmembers
2007 IEEE International Geoscience and Remote Sensing Symposium, 2007A 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 +3 more
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Multi-objective endmember extraction for hyperspectral images
2017 IEEE Congress on Evolutionary Computation (CEC), 2017Endmember 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 +4 more
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Spectral curve-based endmember extraction method
2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2015Most commonly-used methods to determine the number of endmembers and to extract endmember spectra are affected by spectral variability caused by variations in illumination or the physical characteristics of materials. This paper proposes a novel endmember extraction method which can consider the spectral variability.
Tatsumi Uezato +3 more
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Endmember Extraction Technique of HSI
2015Before establishing the linear mixed model and conducting the spectral unmixing operation, it is very necessary to extract the spectral endmember, which acquires the essential priori information for the spectral unmixing.
Liguo Wang, Chunhui Zhao
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