IEICE TRANSACTIONS on Communications
Fuzzy Rule and Bayesian Network Based Line Interpolation for Video Deinterlacing
Summary :
Detecting edge directions and estimating the exact value of a missing line are currently active research areas in deinterlacing processing. This paper proposes a spatial domain fuzzy rule that is based on an interpolation algorithm, which is suitable to the region with high motion or scene change. The algorithm utilizes fuzzy theory to find the most accurate edge direction with which to interpolate missing pixels. The proposed fuzzy direction oriented interpolator operates by identifying small pixel variations in seven orientations (0°, 45°, -45°, 63°, -63°, 72°, and -72°), while using rules to infer the edge direction. The Bayesian network model selects the most suitable deinterlacing method among three deinterlacing methods and it successively builds approximations of the deinterlaced sequence, by evaluating three methods in each condition. Detection and interpolation results are presented. Experimental results show that the proposed algorithm provides a significant improvement over other existing deinterlacing methods. The proposed algorithm is not only for speed, but also effective for reducing deinterlacing artifacts.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E90-B No.6 pp.1495-1507
- Publication Date
- 2007/06/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1093/ietcom/e90-b.6.1495
- Type of Manuscript
- PAPER
- Category
- Multimedia Systems for Communications
Authors
Keyword
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Gwanggil JEON, Jechang JEONG, "Fuzzy Rule and Bayesian Network Based Line Interpolation for Video Deinterlacing" in IEICE TRANSACTIONS on Communications,
vol. E90-B, no. 6, pp. 1495-1507, June 2007, doi: 10.1093/ietcom/e90-b.6.1495.
Abstract: Detecting edge directions and estimating the exact value of a missing line are currently active research areas in deinterlacing processing. This paper proposes a spatial domain fuzzy rule that is based on an interpolation algorithm, which is suitable to the region with high motion or scene change. The algorithm utilizes fuzzy theory to find the most accurate edge direction with which to interpolate missing pixels. The proposed fuzzy direction oriented interpolator operates by identifying small pixel variations in seven orientations (0°, 45°, -45°, 63°, -63°, 72°, and -72°), while using rules to infer the edge direction. The Bayesian network model selects the most suitable deinterlacing method among three deinterlacing methods and it successively builds approximations of the deinterlaced sequence, by evaluating three methods in each condition. Detection and interpolation results are presented. Experimental results show that the proposed algorithm provides a significant improvement over other existing deinterlacing methods. The proposed algorithm is not only for speed, but also effective for reducing deinterlacing artifacts.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e90-b.6.1495/_p
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@ARTICLE{e90-b_6_1495,
author={Gwanggil JEON, Jechang JEONG, },
journal={IEICE TRANSACTIONS on Communications},
title={Fuzzy Rule and Bayesian Network Based Line Interpolation for Video Deinterlacing},
year={2007},
volume={E90-B},
number={6},
pages={1495-1507},
abstract={Detecting edge directions and estimating the exact value of a missing line are currently active research areas in deinterlacing processing. This paper proposes a spatial domain fuzzy rule that is based on an interpolation algorithm, which is suitable to the region with high motion or scene change. The algorithm utilizes fuzzy theory to find the most accurate edge direction with which to interpolate missing pixels. The proposed fuzzy direction oriented interpolator operates by identifying small pixel variations in seven orientations (0°, 45°, -45°, 63°, -63°, 72°, and -72°), while using rules to infer the edge direction. The Bayesian network model selects the most suitable deinterlacing method among three deinterlacing methods and it successively builds approximations of the deinterlaced sequence, by evaluating three methods in each condition. Detection and interpolation results are presented. Experimental results show that the proposed algorithm provides a significant improvement over other existing deinterlacing methods. The proposed algorithm is not only for speed, but also effective for reducing deinterlacing artifacts.},
keywords={},
doi={10.1093/ietcom/e90-b.6.1495},
ISSN={1745-1345},
month={June},}
Copy
TY - JOUR
TI - Fuzzy Rule and Bayesian Network Based Line Interpolation for Video Deinterlacing
T2 - IEICE TRANSACTIONS on Communications
SP - 1495
EP - 1507
AU - Gwanggil JEON
AU - Jechang JEONG
PY - 2007
DO - 10.1093/ietcom/e90-b.6.1495
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E90-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2007
AB - Detecting edge directions and estimating the exact value of a missing line are currently active research areas in deinterlacing processing. This paper proposes a spatial domain fuzzy rule that is based on an interpolation algorithm, which is suitable to the region with high motion or scene change. The algorithm utilizes fuzzy theory to find the most accurate edge direction with which to interpolate missing pixels. The proposed fuzzy direction oriented interpolator operates by identifying small pixel variations in seven orientations (0°, 45°, -45°, 63°, -63°, 72°, and -72°), while using rules to infer the edge direction. The Bayesian network model selects the most suitable deinterlacing method among three deinterlacing methods and it successively builds approximations of the deinterlaced sequence, by evaluating three methods in each condition. Detection and interpolation results are presented. Experimental results show that the proposed algorithm provides a significant improvement over other existing deinterlacing methods. The proposed algorithm is not only for speed, but also effective for reducing deinterlacing artifacts.
ER -
English
