Noise Robust Motion Refinement for Motion Compensated Noise Reduction
Summary :
A motion refinement algorithm is proposed to enhance motion compensated noise reduction (MCNR) efficiency. Instead of the vector with minimum distortion, the vector with minimum distance from motion vectors of neighboring blocks is selected as the best motion vector among vectors which have distortion values within the range set by noise level. This motion refinement finds more accurate motion vectors in the noisy sequences. The MCNR with the proposed algorithm maintains the details of an image sequence very well without blurring and joggling. And it achieves 10% bit-usage reduction or 0.5 dB objective quality enhancement in subsequent video coding.
- Publication
- IEICE TRANSACTIONS on Information Vol.E91-D No.5 pp.1581-1583
- Publication Date
- 2008/05/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e91-d.5.1581
- Type of Manuscript
- LETTER
- Category
- Image Processing and Video Processing
Authors
Keyword
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Jong-Sun KIM, Lee-Sup KIM, "Noise Robust Motion Refinement for Motion Compensated Noise Reduction" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 5, pp. 1581-1583, May 2008, doi: 10.1093/ietisy/e91-d.5.1581.
Abstract: A motion refinement algorithm is proposed to enhance motion compensated noise reduction (MCNR) efficiency. Instead of the vector with minimum distortion, the vector with minimum distance from motion vectors of neighboring blocks is selected as the best motion vector among vectors which have distortion values within the range set by noise level. This motion refinement finds more accurate motion vectors in the noisy sequences. The MCNR with the proposed algorithm maintains the details of an image sequence very well without blurring and joggling. And it achieves 10% bit-usage reduction or 0.5 dB objective quality enhancement in subsequent video coding.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.5.1581/_p
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@ARTICLE{e91-d_5_1581,
author={Jong-Sun KIM, Lee-Sup KIM, },
journal={IEICE TRANSACTIONS on Information},
title={Noise Robust Motion Refinement for Motion Compensated Noise Reduction},
year={2008},
volume={E91-D},
number={5},
pages={1581-1583},
abstract={A motion refinement algorithm is proposed to enhance motion compensated noise reduction (MCNR) efficiency. Instead of the vector with minimum distortion, the vector with minimum distance from motion vectors of neighboring blocks is selected as the best motion vector among vectors which have distortion values within the range set by noise level. This motion refinement finds more accurate motion vectors in the noisy sequences. The MCNR with the proposed algorithm maintains the details of an image sequence very well without blurring and joggling. And it achieves 10% bit-usage reduction or 0.5 dB objective quality enhancement in subsequent video coding.},
keywords={},
doi={10.1093/ietisy/e91-d.5.1581},
ISSN={1745-1361},
month={May},}
Copy
TY - JOUR
TI - Noise Robust Motion Refinement for Motion Compensated Noise Reduction
T2 - IEICE TRANSACTIONS on Information
SP - 1581
EP - 1583
AU - Jong-Sun KIM
AU - Lee-Sup KIM
PY - 2008
DO - 10.1093/ietisy/e91-d.5.1581
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2008
AB - A motion refinement algorithm is proposed to enhance motion compensated noise reduction (MCNR) efficiency. Instead of the vector with minimum distortion, the vector with minimum distance from motion vectors of neighboring blocks is selected as the best motion vector among vectors which have distortion values within the range set by noise level. This motion refinement finds more accurate motion vectors in the noisy sequences. The MCNR with the proposed algorithm maintains the details of an image sequence very well without blurring and joggling. And it achieves 10% bit-usage reduction or 0.5 dB objective quality enhancement in subsequent video coding.
ER -
English
