Concept of Linguistic Variable-Based Fuzzy Ensemble Approach: Application to Interlaced HDTV Sequences

This paper addresses the problem of edge restoration in digital images. Taking advantage of an ensemble approach, multiple type-1 fuzzy filters are combined to reach a decision. The fuzzy logic concept for linguistic variables and possibility theory is discussed with regard to knowledge representati...

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Vydáno v:IEEE transactions on fuzzy systems Ročník 17; číslo 6; s. 1245 - 1258
Hlavní autoři: Gwanggil Jeon, Anisetti, M., Joohyun Lee, Bellandi, V., Damiani, E., Jechang Jeong
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.12.2009
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Deinterlacing
Design engineering
Filters
Fuzzy
fuzzy ensemble approach
Fuzzy logic
Fuzzy set theory
Fuzzy sets
Fuzzy systems
fuzzy weight (FW)
HDTV
Humans
Image restoration
Information technology
Interpolation
linguistic variable
Linguistics
Mathematical models
Pixels
Spatiotemporal phenomena
Studies
type-1 fuzzy system
ISSN:1063-6706, 1941-0034
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Shrnutí:This paper addresses the problem of edge restoration in digital images. Taking advantage of an ensemble approach, multiple type-1 fuzzy filters are combined to reach a decision. The fuzzy logic concept for linguistic variables and possibility theory is discussed with regard to knowledge representation and inference procedures. To improve conventional deinterlacing issues, we adopt type-1 fuzzy set concepts to design a weight-measuring approach. We demonstrate that the fuzzy ensemble approach model is well suited to image processing and provide case studies in the video-deinterlacing field. In our proposed method, five fuzzy membership functions (MFs) of linguistic variable-based fuzzy logic filters are derived from the type-1 (a.k.a. ordinary or primary) fuzzy MF. The weight-measuring process of our proposed model is used to assign weights to six candidate deinterlaced pixels (CDPs) that are interpolated according to edge direction. The use of a different MF for each direction allows the filter to characterize each pixel variation influence independently, according to its direction. The weights from all MFs are multiplied with the CDPs. The results of the empirical trials clearly show that the proposed system can successfully deal with several image types containing motion or detail elements.
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ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2009.2026638