Toward Feature-Preserving 2D and 3D Vector Field Compression

Xin Liang, Hanqi Guo, Sheng Di, Franck Cappello, Mukund Raj, Chunhui Liu, Kenji Ono, Zizhong Chen, Tom Peterka

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

2 被引用数 (Scopus)

抄録

The objective of this work is to develop error-bounded lossy compression methods to preserve topological features in 2D and 3D vector fields. Specifically, we explore the preservation of critical points in piecewise linear vector fields. We define the preservation of critical points as, without any false positive, false negative, or false type change in the decompressed data, (1) keeping each critical point in its original cell and (2) retaining the type of each critical point (e.g., saddle and attracting node). The key to our method is to adapt a vertex-wise error bound for each grid point and to compress input data together with the error bound field using a modified lossy compressor. Our compression algorithm can be also embarrassingly parallelized for large data handling and in situ processing. We benchmark our method by comparing it with existing lossy compressors in terms of false positive/negative/type rates, compression ratio, and various vector field visualizations with several scientific applications.

本文言語英語
ホスト出版物のタイトル2020 IEEE Pacific Visualization Symposium, PacificVis 2020 - Proceedings
編集者Fabian Beck, Jinwook Seo, Chaoli Wang
出版社IEEE Computer Society
ページ81-90
ページ数10
ISBN(電子版)9781728156972
DOI
出版ステータス出版済み - 6 2020
イベント13th IEEE Pacific Visualization Symposium, PacificVis 2020 - Tianjin, 中国
継続期間: 4 14 20204 17 2020

出版物シリーズ

名前IEEE Pacific Visualization Symposium
2020-June
ISSN(印刷版)2165-8765
ISSN(電子版)2165-8773

会議

会議13th IEEE Pacific Visualization Symposium, PacificVis 2020
国/地域中国
CityTianjin
Period4/14/204/17/20

All Science Journal Classification (ASJC) codes

  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • コンピュータ ビジョンおよびパターン認識
  • ハードウェアとアーキテクチャ
  • ソフトウェア

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