Algebraic models and methods of computer image processing. Part 1. Multiplet models of multichannel images
| Autor: | E. Ostheimer, E. V. Kokh, V. G. Labunets |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Computer science Image processing 02 engineering and technology Quantitative Biology::Other 020901 industrial engineering & automation hypercomplex algebra Animal brain 0202 electrical engineering electronic engineering information engineering lcsh:Information theory lcsh:QC350-467 Electrical and Electronic Engineering Algebraic number Commutative property multichannel images Hypercomplex number Pixel Hyperspectral imaging lcsh:Q350-390 Atomic and Molecular Physics and Optics Computer Science Applications image processing Algebra 020201 artificial intelligence & image processing Complex number lcsh:Optics. Light |
| Zdroj: | Компьютерная оптика, Vol 42, Iss 1, Pp 84-95 (2018) |
| ISSN: | 2412-6179 0134-2452 |
| Popis: | We present a new theoretical framework for multichannel image processing using commutative hypercomplex algebras. Hypercomplex algebras generalize the algebras of complex numbers. The main goal of the work is to show that hypercomplex algebras can be used to solve problems of multichannel (color, multicolor, and hyperspectral) image processing in a natural and effective manner. In this work, we suppose that the animal brain operates with hypercomplex numbers when processing multichannel retinal images. In our approach, each multichannel pixel is considered not as an K–D vector, but as an K–D hypercomplex number, where K is the number of different optical channels. The aim of this part is to present algebraic models of subjective perceptual color, multicolor and multichannel spaces. |
| Databáze: | OpenAIRE |
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