Interlaced-to-progressive conversion using adaptive projection-based global and representative local motion estimation

Young Duk Kim, Joonyoung Chang, Gun Shik Shin, Moon Gi Kang

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

We propose a motion-compensation-based deinterlacing algorithm using global and representative local motion estimation. The proposed algorithm first divides an entire image into five regions of interest (ROIs) according to the temporally predicted motion type (i.e., global or local) and the spatial position. One of them is for global motion estimation and the others are for local motion estimation. Then, dominant motions of respective ROIs are found by adaptive projection approach. The adaptive projection method not only estimates dominant local motions with low computational cost, but also ensures consistent global motion estimation. Using the estimated motion vectors, adaptive two-field bidirectional motion compensation is performed. The arbitration rules, measuring the reliability of motion compensation accurately, produce high-quality deinterlaced frames by effectively combining the results of motion compensation and the stable intrafield deinterlacing. Experimental results show that the proposed deinterlacing algorithm provides better image quality than the existing algorithms in both subjective and objective measures.

Original languageEnglish
Article number023008
JournalJournal of Electronic Imaging
Volume17
Issue number2
DOIs
Publication statusPublished - 2008

Bibliographical note

Funding Information:
This work has been supported by System LSI division, Samsung Electronics Co., Ltd. and Seoul Future Contents Convergence (SFCC) Cluster established by Seoul Industry-Academy-Research Cooperation Project at Yonsei University.

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Computer Science Applications
  • Electrical and Electronic Engineering

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