Institute of Information Theory and Automation

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Conference Paper (international conference)

Optimized Texture Spectral Similarity Criteria

Havlíček Michal, Haindl Michal

: Advances in Computational Collective Intelligence, p. 644-655 , Eds: Wojtkiewicz Krystian, Treur Jan, Pimenidis Elias, Maleszka Marcin

: International Conference on Computational Collective Intelligence 2021 /13./, (Kallithea, Rhodes, GR, 20210929)

: GA19-12340S, GA ČR

: Texture spectral similarity criterion, Bidirectional Texture Function, hyperspectral data, texture modeling

: 10.1007/978-3-030-88113-9_52

: http://library.utia.cas.cz/separaty/2021/RO/haindl-0546216.pdf

(eng): This paper introduces an accelerated algorithm for evaluating criteria for comparing the spectral similarity of color, Bidirectional Texture Functions (BTF), and hyperspectral textures. The criteria credibly compare texture pixels by simultaneously considering the pixels with similar values and their mutual ratios. Such a comparison can determine the optimal modeling or acquisition setup by comparing the original data with their synthetic simulations. Other applications of the criteria can be spectral-based texture retrieval or classification. Together with existing alternatives, the suggested methods were extensively tested and compared on a wide variety of color, BTF, and hyper-spectral textures. The methods' performance quality was examined in a long series of specially designed experiments where proposed ones outperform all tested alternatives.

: BD

: 20202

2019-01-07 08:39