Paper Info
Title
In-loop denoising of reference frames for lossless coding of noisy image sequences
Abstract
The major gain in video coding applications compared to single image coding is the use of temporal prediction, which exploits the correlation between adjacent frames. However, in high quality video coding, especially lossless video coding, the compression gain of P-frames over I-Frames becomes very small. The reason for that is that the reference frame for inter prediction is not good enough, and therefore the amount of inter-predicted blocks in a P-Frame becomes relatively small compared to the number of intra-predicted blocks. In order to generate a better predictor for inter-prediction, we propose to remove additive noise from the reference frame using an adaptive Wiener filter. This way, we could achieve a maximum compression gain of 4.6% and an average compression gain of 3.3% in contrast to the H.264/AVC standard for lossless coding of high quality image sequences without affecting the encoding time noticeably.
Year
DOI
Venue
2010
10.1109/ICIP.2010.5654136
Image Processing
Keywords
Field
DocType
Wiener filters,adaptive filters,encoding,image denoising,image sequences,video coding,H.264/AVC standard,adaptive Wiener filter,additive noise,adjacent frame,compression gain,image coding,in-loop denoising,interprediction,intrapredicted block,lossless video coding,noisy image sequence,reference frame,temporal prediction,Lossless Video Compression,Motion Compensated Prediction,Predictor Denoising
Computer vision,Entropy encoding,Coding tree unit,Pattern recognition,Lossy compression,Context-adaptive variable-length coding,Computer science,Motion compensation,Sub-band coding,Artificial intelligence,Data compression,Context-adaptive binary arithmetic coding
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-7993-1
978-1-4244-7993-1
7
PageRank 
References 
Authors
0.92
6
4
Name
Order
Citations
PageRank
Wige, E.1101.68
Peter Amon220123.28
Andreas Hutter329729.47
André Kaup4101.33