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A Psychophysical Evaluation of Texture Degradation Descriptors

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F10%3A00346556" target="_blank" >RIV/67985556:_____/10:00346556 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Psychophysical Evaluation of Texture Degradation Descriptors

  • Original language description

    Delivering a digital 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 illumination dependent 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 set dependently on the actual material. We propose a set of statistical descriptors motivatedby standard textural features, and psychophysically evaluate their performance on three subtle artificial texture visual degradations. We tested the five types of descriptors on five different textures and combination of thirteen surface shapes and twoilluminations. We have found that descriptors based on two-dimensional causal auto-regressive model, have the highest correlation with the psychophysical results.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BD - Information theory

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2010

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Structural, Syntactic, and Statistical Pattern Recognition

  • ISBN

    978-3-642-14979-5

  • ISSN

  • e-ISSN

  • Number of pages

    11

  • Pages from-to

  • Publisher name

    Springer Berlin / Heidelberg

  • Place of publication

    Berlin / Heidelberg

  • Event location

    Cesme, Izmir

  • Event date

    Aug 18, 2010

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article