Performance of optical flow techniques
International Journal of Computer Vision
A feature-based algorithm for detecting and classifying production effects
Multimedia Systems
Compression with Side Information Using Turbo Codes
DCC '02 Proceedings of the Data Compression Conference
Rate-adaptive codes for distributed source coding
Signal Processing - Special section: Distributed source coding
Wyner-Ziv coding of video with unsupervised motion vector learning
Image Communication
Advanced side information creation techniques and framework for Wyner-Ziv video coding
Journal of Visual Communication and Image Representation
Improved virtual channel noise model for transform domain Wyner-Ziv video coding
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Dynamic quality control for transform domain Wyner-Ziv video coding
Journal on Image and Video Processing - Special issue on distributed video coding
IEEE Transactions on Circuits and Systems for Video Technology
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
Prioritized side information correction for distributed video coding
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
Performance improvement of distributed video coding by using block mode selection
Proceedings of the international conference on Multimedia
Journal of Visual Communication and Image Representation
The rate-distortion function for source coding with side information at the decoder
IEEE Transactions on Information Theory
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
FSIM: A Feature Similarity Index for Image Quality Assessment
IEEE Transactions on Image Processing
Hi-index | 0.00 |
In this paper, we propose a perceptual-based distributed video coding (DVC) technique. Unlike traditional video codecs, DVC applies video prediction process at the decoder side using previously received frames. The predicted video frames (i.e., side information) contain prediction errors. The encoder then transmits error-correcting parity bits to the decoder to reconstruct the video frames from side information. However, channel codes based on i.i.d. noise models are not always efficient in correcting video prediction errors. In addition, some of the prediction errors do not cause perceptible visual distortions. From perceptual coding point of view, there is no need to correct such errors. This paper proposes a scheme for the decoder to perform perceptual quality analysis on the predicted side information. The decoder only requests parity bits to correct visually sensitive errors. More importantly, with the proposed technique, key frames can be encoded at higher rates while still maintaining consistent visual quality across the video sequence. As a result, even the objective PSNR measure of the decoded video sequence will increase too. Experimental results show that the proposed technique improves the R-D performance of a transform domain DVC codec both subjectively and objectively. Comparisons with a well-known DVC codec show that the proposed perceptual-based DVC coding scheme is very promising for distributed video coding framework.