QuadStack: An Efficient Representation and Direct Rendering of Layered Datasets

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00343857" target="_blank" >RIV/68407700:21230/21:00343857 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/TVCG.2020.2981565" target="_blank" >https://doi.org/10.1109/TVCG.2020.2981565</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TVCG.2020.2981565" target="_blank" >10.1109/TVCG.2020.2981565</a>

Jazyk výsledku

angličtina

Název v původním jazyce

QuadStack: An Efficient Representation and Direct Rendering of Layered Datasets

Popis výsledku v původním jazyce

We introduce QuadStack, a novel algorithm for volumetric data compression and direct rendering. Our algorithm exploits the data redundancy often found in layered datasets that are common in science and engineering fields such as geology, biology, mechanical engineering, medicine, etc. QuadStack first compresses the volumetric data into vertical stacks that are then compressed into a quadtree that identifies and represents the layered structures at the internal nodes. The associated data (color, material, density, etc.) and shape of these layer structures are decoupled and encoded independently, leading to high compression rates (4x to 45x) of the original voxel model memory footprint in our experiments). We also introduce an algorithm for value retrieving from the QuadStack representation and we show that the access has logarithmic complexity. Because of the fast access, QuadStack is suitable for efficient data representation and direct rendering and we show that our GPU implementation performs comparable in speed with the state-of-the-art algorithms (18-79 MRays/s in our implementation), while maintaining a significantly smaller memory footprint

Název v anglickém jazyce

QuadStack: An Efficient Representation and Direct Rendering of Layered Datasets

Popis výsledku anglicky

We introduce QuadStack, a novel algorithm for volumetric data compression and direct rendering. Our algorithm exploits the data redundancy often found in layered datasets that are common in science and engineering fields such as geology, biology, mechanical engineering, medicine, etc. QuadStack first compresses the volumetric data into vertical stacks that are then compressed into a quadtree that identifies and represents the layered structures at the internal nodes. The associated data (color, material, density, etc.) and shape of these layer structures are decoupled and encoded independently, leading to high compression rates (4x to 45x) of the original voxel model memory footprint in our experiments). We also introduce an algorithm for value retrieving from the QuadStack representation and we show that the access has logarithmic complexity. Because of the fast access, QuadStack is suitable for efficient data representation and direct rendering and we show that our GPU implementation performs comparable in speed with the state-of-the-art algorithms (18-79 MRays/s in our implementation), while maintaining a significantly smaller memory footprint

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

IEEE Transactions on Visualization and Computer Graphics

ISSN

1077-2626

e-ISSN

1941-0506

Svazek periodika

27

Číslo periodika v rámci svazku

9

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

12

Strana od-do

3733-3744

Kód UT WoS článku

000679532000010

EID výsledku v databázi Scopus

2-s2.0-85111772911