A motion-adaptive deinterlacer via hybrid motion detection and edge-pattern recognition

Ming Jiun Wang, Gwo Giun Lee, Hsin Te Li, He Yuan Lin

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion, edges, textures, and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover, predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences.

Original languageEnglish
Article number741290
JournalEurasip Journal on Image and Video Processing
Volume2008
DOIs
Publication statusPublished - 2008 May 26

Fingerprint

Pattern recognition
Interpolation
Textures
Processing
Adaptive algorithms
Pixels
Data storage equipment
Costs

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Electrical and Electronic Engineering

Cite this

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abstract = "A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion, edges, textures, and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover, predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences.",
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A motion-adaptive deinterlacer via hybrid motion detection and edge-pattern recognition. / Wang, Ming Jiun; Lee, Gwo Giun; Li, Hsin Te; Lin, He Yuan.

In: Eurasip Journal on Image and Video Processing, Vol. 2008, 741290, 26.05.2008.

Research output: Contribution to journalArticle

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