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SSPR
2010
Springer

A Psychophysical Evaluation of Texture Degradation Descriptors

9 years 10 months ago
A Psychophysical Evaluation of Texture Degradation Descriptors
Delivering digitally a realistic appearance of materials is one of the most difficult tasks of computer vision. Accurate representation of surface texture can be obtained by means of view- and illuminationdependent textures. However, this kind of appearance representation produces massive datasets so their compression is inevitable. For optimal visual performance of compression methods, their parameters should be tuned to a specific material. We propose a set of statistical descriptors motivated by textural features, and psychophysically evaluate their performance on three subtle artificial degradations of textures appearance. We tested five types of descriptors on five different textures and combination of thirteen surface shapes and two illuminations. We found that descriptors based on a two-dimensional causal auto-regressive model, have the highest correlation with the psychophysical results, and so can be used for automatic detection of subtle changes in rendered textured surf...
Jirí Filip, Pavel Vácha, Michal Hain
Added 30 Jan 2011
Updated 30 Jan 2011
Type Journal
Year 2010
Where SSPR
Authors Jirí Filip, Pavel Vácha, Michal Haindl, Patrick R. Green
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