Mutual Information-Based Texture Spectral Similarity Criterion

0510483 - ÚTIA 2020 RIV CH eng C - Conference Paper (international conference)
Haindl, Michal - Havlíček, Michal
Mutual Information-Based Texture Spectral Similarity Criterion.
Advances in Visual Computing : 14th International Symposium on Visual Computing (ISVC 2019). Cham: Springer, 2019 - (Bebis, G.; Boyle, R.; Parvin, B.; Koracin, D.), s. 302-314, č. článku 23. Lecture Notes in Computer Science, 11844. ISBN 978-3-030-33719-3. ISSN 0302-9743. E-ISSN 1611-3349.
[International Symposium on Visual Computing (ISVC 2019) /14./. Lake Tahoe (US), 07.10.2019-09.10.2019]
R&D Projects: GA ČR(CZ) GA19-12340S
Institutional support: RVO:67985556
Keywords : spectral similarity criterion * Bidirectional Texture Functions * texture * mutual information
OECD category: Automation and control systems
http://library.utia.cas.cz/separaty/2019/RO/haindl-0510483.pdf

Fast novel texture spectral similarity criterion, capable of assessing spectral modeling resemblance of color and Bidirectional Texture Functions (BTF) textures, is presented. The criterion reliably compares the multi-spectral pixel values of two textures, and thus it allows to assist an optimal modeling or acquisition setup development by comparing the original data with its synthetic simulations. The suggested criterion, together with existing alternatives, is extensively tested in a long series of thousands specially designed monotonically degrading experiments moreover, successfully compared on a wide variety of color and BTF textures.
Permanent Link: http://hdl.handle.net/11104/0302679