New global motion compensated de-interlacing algorithm based on horizontal and vertical patterns

Min Kyu Park, Moon Gi Kang

Research output: Contribution to journalConference article

2 Citations (Scopus)

Abstract

In this paper, we propose a robust deinterlacing algorithm which combines edge dependent interpolation (EDI) and global motion compensation (GMC). Generally, EDI algorithm shows a visually better performance than any other deinterlacing algorithm using one field. However, due to the restriction of information in one field, a high quality progressive image from interlaced sources cannot be acquired by intrafield methods. Hence, proposed algorithm makes use of mixing process of EDI and GMC. In order to obtain the best result, adaptive thresholding algorithm for detecting the failure of GMC is proposed. Experimental results indicate that the proposed algorithm outperforms conventional approaches with respect to both objective and subjective criteria.

Original languageEnglish
Pages (from-to)III345-III348
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
Publication statusPublished - 2004 Sep 28
EventProceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada
Duration: 2004 May 172004 May 21

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Motion compensation
Interpolation
Adaptive algorithms

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

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abstract = "In this paper, we propose a robust deinterlacing algorithm which combines edge dependent interpolation (EDI) and global motion compensation (GMC). Generally, EDI algorithm shows a visually better performance than any other deinterlacing algorithm using one field. However, due to the restriction of information in one field, a high quality progressive image from interlaced sources cannot be acquired by intrafield methods. Hence, proposed algorithm makes use of mixing process of EDI and GMC. In order to obtain the best result, adaptive thresholding algorithm for detecting the failure of GMC is proposed. Experimental results indicate that the proposed algorithm outperforms conventional approaches with respect to both objective and subjective criteria.",
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