Open AccessElimination of information redundancy of hyperspectral images using the “well-adapted” basis method
Author(s) -
Dmitriy Vasin,
Владимир Громов,
Pavel Pakhomov
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1368/3/032025
Subject(s) - redundancy (engineering) , hyperspectral imaging , computer science , basis (linear algebra) , artificial intelligence , chebyshev filter , data redundancy , computer vision , graphics , pattern recognition (psychology) , algorithm , mathematics , computer graphics (images) , geometry , operating system
The paper considers some issues of eliminating information redundancy of hyperspectral images (HSI). The characteristic properties of the HSI are listed, a brief description of the existing HSI compression methods is given. The possibility of using local, homogeneous “well-adapted” basis functions (LHWABF) to eliminate information redundancy and adaptive compression of the HSI is considered. An algorithm for constructing a LHWABF system for the HSI based on the Chebyshev approximation is proposed. The results of computational experiments, including the use of a graphics processor, are presented. The effectiveness of the proposed method of adaptive compression HSI is shown.