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Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F04%3A03099341" target="_blank" >RIV/68407700:21230/04:03099341 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

BTF Image Space Utmost Compression and Modelling Method

Popis výsledku v původním jazyce

The bidirectional texture function (BTF) describes texture appearance variations due to varying illumination and viewing conditions. This function is acquired by large number of measurements for all possible combinations of illumination and viewing positions hence some compressed representation of these huge BTF texture data spaces is obviously inevitable. In this paper we present a novel efficient probabilistic model-based method for multispectral BTF texture compression which simultaneously allows itsefficient modelling.This representation model is capable of seamless BTF space enlargement and direct implementation inside the graphical card processing unit.The analytical step of the algorithm starts with BTF texture surface estimation followed by the spatial factorization of an input multispectral texture image. Single band-limited factors are independently modelled by their dedicated 3D causal autoregressive models (CAR). We estimate an optimal contextual neighbourhood and p.

Název v anglickém jazyce

BTF Image Space Utmost Compression and Modelling Method

Popis výsledku anglicky

The bidirectional texture function (BTF) describes texture appearance variations due to varying illumination and viewing conditions. This function is acquired by large number of measurements for all possible combinations of illumination and viewing positions hence some compressed representation of these huge BTF texture data spaces is obviously inevitable. In this paper we present a novel efficient probabilistic model-based method for multispectral BTF texture compression which simultaneously allows itsefficient modelling.This representation model is capable of seamless BTF space enlargement and direct implementation inside the graphical card processing unit.The analytical step of the algorithm starts with BTF texture surface estimation followed by the spatial factorization of an input multispectral texture image. Single band-limited factors are independently modelled by their dedicated 3D causal autoregressive models (CAR). We estimate an optimal contextual neighbourhood and p.

Druh

A - Audiovizuální tvorba

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2004

Kód důvěrnosti údajů

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

ISBN

0-7695-2128-2

Místo vydání

London

Název nakladatele resp. objednatele

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Verze

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Identifikační číslo nosiče

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