Texture Spectral Similarity Criteria

0508907 - ÚTIA 2020 RIV GB eng J - Journal Article
Havlíček, Michal - Haindl, Michal
Texture Spectral Similarity Criteria.
IET Image Processing. Roč. 13, č. 11 (2019), s. 1998-2007. ISSN 1751-9659. E-ISSN 1751-9667
R&D Projects: GA ČR(CZ) GA19-12340S
Institutional support: RVO:67985556
Keywords : Spectral similarity criterion * bidirectional Texture Function * hyper-spectral data * texture modelling
OECD category: Automation and control systems
Impact factor: 1.995, year: 2019
Method of publishing: Limited access
http://library.utia.cas.cz/separaty/2019/RO/haindl-0508907.pdf https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0250

New similarity criteria capable of assessing spectral modelling plausibility of colour, Bidirectional Texture Functions (BTF), and hyper-spectral textures are presented. The criteria credibly compare the multi-spectral pixel values of the textures. They simultaneously consider the pixels of similar values and their mutual ratios. It allows support of the optimal modelling or acquisition setup development by comparing the original data with its synthetic simulations. Analytical applications of the criteria can be spectral-based texture retrieval or classification. The suggested criteria together with existing alternatives are extensively tested and compared on a wide variety of colour, BTF, and hyper-spectral textures. The performance quality of the criteria is examined in a long series of thousands specially designed monotonically degrading experiments where proposed ones outperform all tested alternatives.
Permanent Link: http://hdl.handle.net/11104/0299790