Please use this identifier to cite or link to this item:
Title: Adaptive rounding operator for efficient Wyner-Ziv video coding
Authors: Micallef, Jeffrey J.
Farrugia, Reuben A.
Debono, Carl James
Keywords: Video compression
Correlation (Statistics) -- Computer programs
Signal processing
Issue Date: 2013
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Micallef, J. J., Farrugia, R. A., & Debono, C. J. (2013). Adaptive rounding operator for efficient Wyner-Ziv video coding. Visual Communications and Image Processing (VCIP), Kuching. 1-6.
Abstract: The Distributed Video Coding (DVC) paradigm can theoretically reach the same coding efficiencies of predictive block-based video coding schemes, like H.264/AVC. However, current DVC architectures are still far from this ideal performance. This is mainly attributed to inaccuracies in the Side Information (SI) predicted at the decoder. The work in this paper presents a coding scheme which tries to avoid mismatch in the SI predictions caused by small variations in light intensity. Using the appropriate rounding operator for every coefficient, the proposed method significantly reduces the correlation noise between the Wyner-Ziv (WZ) frame and the corresponding SI, achieving higher coding efficiencies. Experimental results demonstrate that the average Peak Signal-to-Noise Ratio (PSNR) is improved by up to 0.56dB relative to the DISCOVER codec.
Description: The research work disclosed in this publication is partially funded by the Strategic Educational Pathways Scholarship Scheme (Malta). The scholarship is part-financed by the European Union – European Social Fund. (ESF 1.25).
Appears in Collections:Scholarly Works - FacICTCCE

Files in This Item:
File Description SizeFormat 
OA Conference paper - Adaptive rounding operator for efficient Wyner-Ziv video coding.2-7.pdfAdaptive rounding operator for efficient Wyner-Ziv video coding540.07 kBAdobe PDFView/Open

Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.