Merged Multiresolution Hierarchies for Shadow Map Compression

Multiresolution Hierarchies (MH) and Directed Acyclic Graphs (DAG) are two recent approaches for the compression of high‐resolution shadow information. In this paper, we introduce Merged Multiresolution Hierarchies (MMH), a novel data structure that unifies both concepts. An MMH leverages both hiera...

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Vydáno v:Computer graphics forum Ročník 35; číslo 7; s. 383 - 390
Hlavní autoři: Scandolo, Leonardo, Bauszat, Pablo, Eisemann, Elmar
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Blackwell Publishing Ltd 01.10.2016
Témata:
Algorithms
Analogies
Analysis
and texture
Categories and Subject Descriptors (according to ACM CCS)
Compressing
Data compression
Graph theory
Hierarchies
Homogeneity
I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism-Color
I.3.7 [Computer Graphics]: Three‐Dimensional Graphics and Realism—Color, shading, shadowing, and texture
I.4.2 [Computer Graphics]: Compression (Coding)-Exact coding
Image processing systems
Representations
shading
shadowing
Shadows
Studies
ISSN:0167-7055, 1467-8659
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Popis
Shrnutí:Multiresolution Hierarchies (MH) and Directed Acyclic Graphs (DAG) are two recent approaches for the compression of high‐resolution shadow information. In this paper, we introduce Merged Multiresolution Hierarchies (MMH), a novel data structure that unifies both concepts. An MMH leverages both hierarchical homogeneity exploited in MHs, as well as topological similarities exploited in DAG representations. We propose an efficient hash‐based technique to quickly identify and remove redundant subtree instances in a modified relative MH representation. Our solution remains lossless and significantly improves the compression rate compared to both preceding shadow map compression algorithms, while retaining the full run‐time performance of traditional MH representations.
Bibliografie:Supporting InformationSupporting Information
istex:9E306B8ED952273DBA075A753A89882A4AA05E39
ark:/67375/WNG-5LJ1305N-R
ArticleID:CGF13035
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.13035