Type-2 fuzzy image enhancement

P. Ensafi; H. R. Tizhoosh

doi:10.1007/11559573_20

Type-2 fuzzy image enhancement

P. Ensafi, H. R. Tizhoosh

Artificial Intelligence and Informatics

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

Abstract

In the classical image processing paradigm, the fundamental idea of image enhancement is to produce a new image such that it exposes information for analysis more than the original image. Fuzzy Logic methods are one of valuable and frequently used techniques among many other image enhancement approaches. In this work we demonstrate that a type-2 fuzzy logic system is able to perform image contrast enhancement better than its type-1 counterpart. Examples are provided. Results are discussed.

Original language	English (US)
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages	159-166
Number of pages	8
DOIs	https://doi.org/10.1007/11559573_20
State	Published - 2005
Event	2nd International Conference on Image Analysis and Recognition, ICIAR 2005 - Toronto, Canada Duration: Sep 28 2005 → Sep 30 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3656 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Conference on Image Analysis and Recognition, ICIAR 2005
Country/Territory	Canada
City	Toronto
Period	9/28/05 → 9/30/05

Keywords

Fuzzy image enhancement
Locally adaptive techniques
Type-2 Fuzzy Sets

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/11559573_20

Cite this

Ensafi, P., & Tizhoosh, H. R. (2005). Type-2 fuzzy image enhancement. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 159-166). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3656 LNCS). https://doi.org/10.1007/11559573_20

Type-2 fuzzy image enhancement. / Ensafi, P.; Tizhoosh, H. R.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2005. p. 159-166 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3656 LNCS).

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

Ensafi, P & Tizhoosh, HR 2005, Type-2 fuzzy image enhancement. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3656 LNCS, pp. 159-166, 2nd International Conference on Image Analysis and Recognition, ICIAR 2005, Toronto, Canada, 9/28/05. https://doi.org/10.1007/11559573_20

Ensafi P, Tizhoosh HR. Type-2 fuzzy image enhancement. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2005. p. 159-166. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11559573_20

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Type-2 fuzzy image enhancement

Abstract

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Keywords

ASJC Scopus subject areas

Access to Document

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