Fast LIC image generation based on significance map

Li Chen; Issei Fujishiro; Qunshen G. Peng

doi:10.1007/3-540-39999-2_52

Fast LIC image generation based on significance map

Li Chen, Issei Fujishiro, Qunshen G. Peng

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

Although texture-based methods provide a very promising way to visualize 3D vector fields, they are very time-consuming. In this paper, we introduce the notion of “significance map”, and describe how significance values are derived from the intrinsic properties of a vector field. Based on the significance map, we propose techniques to accelerate the generation of a line integral convolution (LIC) texture image, to highlight important structures in a vector field, and to generate an LIC texture image with different granularities. Also, we describe how to implement our method in a parallel environment. Experimental results illustrate the feasibility of our method.

Original language	English
Title of host publication	High Performance Computing - 3rd International Symposium, ISHPC 2000, Proceedings
Editors	Mateo Valero, Kazuki Joe, Masaru Kitsuregawa, Hidehiko Tanaka
Publisher	Springer Verlag
Pages	537-546
Number of pages	10
ISBN (Print)	9783540411284
DOIs	https://doi.org/10.1007/3-540-39999-2_52
Publication status	Published - 2000
Externally published	Yes
Event	3rd International Symposium on High Performance Computing, ISHPC 2000 - Tokyo, Japan Duration: 2000 Oct 16 → 2000 Oct 18

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1940
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	3rd International Symposium on High Performance Computing, ISHPC 2000
Country/Territory	Japan
City	Tokyo
Period	00/10/16 → 00/10/18

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/3-540-39999-2_52

Cite this

Chen, L., Fujishiro, I., & Peng, Q. G. (2000). Fast LIC image generation based on significance map. In M. Valero, K. Joe, M. Kitsuregawa, & H. Tanaka (Eds.), High Performance Computing - 3rd International Symposium, ISHPC 2000, Proceedings (pp. 537-546). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1940). Springer Verlag. https://doi.org/10.1007/3-540-39999-2_52

Fast LIC image generation based on significance map. / Chen, Li; Fujishiro, Issei; Peng, Qunshen G.

High Performance Computing - 3rd International Symposium, ISHPC 2000, Proceedings. ed. / Mateo Valero; Kazuki Joe; Masaru Kitsuregawa; Hidehiko Tanaka. Springer Verlag, 2000. p. 537-546 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1940).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chen, L, Fujishiro, I & Peng, QG 2000, Fast LIC image generation based on significance map. in M Valero, K Joe, M Kitsuregawa & H Tanaka (eds), High Performance Computing - 3rd International Symposium, ISHPC 2000, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1940, Springer Verlag, pp. 537-546, 3rd International Symposium on High Performance Computing, ISHPC 2000, Tokyo, Japan, 00/10/16. https://doi.org/10.1007/3-540-39999-2_52

Chen L, Fujishiro I, Peng QG. Fast LIC image generation based on significance map. In Valero M, Joe K, Kitsuregawa M, Tanaka H, editors, High Performance Computing - 3rd International Symposium, ISHPC 2000, Proceedings. Springer Verlag. 2000. p. 537-546. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-39999-2_52

Chen, Li ; Fujishiro, Issei ; Peng, Qunshen G. / Fast LIC image generation based on significance map. High Performance Computing - 3rd International Symposium, ISHPC 2000, Proceedings. editor / Mateo Valero ; Kazuki Joe ; Masaru Kitsuregawa ; Hidehiko Tanaka. Springer Verlag, 2000. pp. 537-546 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Although texture-based methods provide a very promising way to visualize 3D vector fields, they are very time-consuming. In this paper, we introduce the notion of “significance map”, and describe how significance values are derived from the intrinsic properties of a vector field. Based on the significance map, we propose techniques to accelerate the generation of a line integral convolution (LIC) texture image, to highlight important structures in a vector field, and to generate an LIC texture image with different granularities. Also, we describe how to implement our method in a parallel environment. Experimental results illustrate the feasibility of our method.",

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Fast LIC image generation based on significance map

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