A novel de-interlacing technique using bi-directional motion estimation

Yoon Kim, Kang Sun Choi, Jae Young Pyun, Byung Tae Choi, Sung Jea Ko

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

A novel de-interlacing algorithm is proposed to accomplish high quality video format conversion. In the proposed scheme, bi-directional motion estimation (ME) is performed between the same parity fields, i.e., the previous and next fields. The bi-directional motion estimation is composed of initial motion vector estimation, motion vector smoothing using motion vector field segmentation, and motion vector refinement in the interpolated field. The proposed method using bidirectional motion estimation can produce robust motion vectors in sequences with camera motion such as panning and zooming. Experimental results show a high visual performance of the proposed de-interlacing algorithm.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsVipin Kumar, Marina L. Gavrilova, Chih Jeng Kenneth Tan, Pierre L’Ecuyer, Chih Jeng Kenneth Tan
PublisherSpringer Verlag
Pages957-966
Number of pages10
ISBN (Print)3540401555, 9783540448396
DOIs
Publication statusPublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2667
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kim, Y., Choi, K. S., Pyun, J. Y., Choi, B. T., & Ko, S. J. (2003). A novel de-interlacing technique using bi-directional motion estimation. In V. Kumar, M. L. Gavrilova, C. J. K. Tan, P. L’Ecuyer, & C. J. K. Tan (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 957-966). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2667). Springer Verlag. https://doi.org/10.1007/3-540-44839-x_101