Proceedings ArticleDOI
Geometrical Aspects of Correlation-Extreme Methods for Object Recognition and HSI Compression
TLDR
The results of the studies of the correlation-extreme methods for signature recognition and methods for compression of hyperspectral images (HSI) with controlled losses depending on the templates selection technique, on the threshold value, onThe type of threshold used and on the selected type of invariant transformation are presented.Abstract:
This paper presents the results of the studies of the correlation-extreme methods for signature recognition and methods for compression of hyperspectral images (HSI) with controlled losses depending on the templates selection technique, on the threshold value, on the type of threshold used and on the selected type of invariant transformation. Recommendations are formulated for the selection of the said parameters in order to more effectively form a set of templates. Experiments have been carried out on real HSI fragments.read more
Citations
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Journal ArticleDOI
Optimization of the Composition of Standards in Recognition and Compression Algorithms of Hyperspectral Images
TL;DR: A solution to the problem of minimizing the number of standards in order to increase both the compression coefficient of hyperspectral images (HSI) and the speed of correlation extreme compression methods (CEM).
References
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The sphere packing problem in dimension 24
TL;DR: In this article, it was shown that the Leech lattice is the densest packing of congruent spheres in twenty-four dimensions and that it is the unique optimal periodic packing.
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Vegetation type recognition in hyperspectral images using a conjugacy indicator
S. A. Bibikov,Photonics” Ras, Molodogvardeyskaya , , Samara, Russia,Nikolay L. Kazanskiy,Vladimir Fursov +3 more
Journal ArticleDOI
Комплексный анализ и мониторинг состояния окружающей среды на основе данных ДЗЗ
TL;DR: A pilot version of the concept of geographic information system (GIS) and an appropriate database management system (DBMS) was built and implemented, which provides monitoring and is based on the prioritized processing and storage of the HSI, which serve as a data source for the system.
Journal ArticleDOI
Study of the classification efficiency of difficult-to-distinguish vegetation types using hyperspectral data
TL;DR: In this paper, the effectiveness of spectral and spectral-spatial classification of hyperspectral data has been investigated using various spectral and spatial features, including minimum distance, support vector machine, mahalanobis distance and maximum likelihood methods.