Designing of a type-2 fuzzy logic filter for improving edge-preserving restoration of interlaced-to-progressive conversion

Gwanggil Jeon, Marco Anisetti, Valerio Bellandi, Ernesto Damiani, Jechang Jeong

Research output: Contribution to journalArticlepeer-review

62 Scopus citations

Abstract

This paper focuses on recently advanced fuzzy models and the application of type-2 fuzzy sets in video deinterlacing. The final goal of the proposed deinterlacing algorithm is to exactly determine an unknown pixel value while preserving the edges and details of the image. To begin, we will discuss some artefacts of spatial, temporal, and spatio-temporal domain deinterlacing methods. In order to address the aforementioned issues, we adopted type-2 fuzzy sets concepts to design a weight evaluating approach. In the proposed method, the upper and lower fuzzy membership functions of the type-2 fuzzy logic filters are derived from the type-1 (or primary) fuzzy membership function. The weights from upper and lower membership functions are considered to be multiplied with the candidate deinterlaced pixels. Experimental results proved that the performance of the proposed method was superior, both objectively and subjectively to other different conventional deinterlacing methods. Moreover, the proposed method preserved the smoothness of the original image edges and produced a high-quality progressive image.

Original languageBritish English
Pages (from-to)2194-2207
Number of pages14
JournalInformation Sciences
Volume179
Issue number13
DOIs
StatePublished - 13 Jun 2009

Keywords

  • Deinterlacing
  • Fuzzy weight
  • Image enhancement
  • Image restoration
  • Type-2 fuzzy system

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