Evaluating a feedback channel based transform domain Wyner-Ziv video codec
Image Communication
Accurate Correlation Modeling for Transform-Domain Wyner-Ziv Video Coding
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Introducing skip mode in distributed video coding
Image Communication
Refining side information for improved transform domain Wyner-Ziv video coding
IEEE Transactions on Circuits and Systems for Video Technology
Crossover probability estimation using mean-intrinsic-LLR of LDPC syndrome
IEEE Communications Letters
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
Distributed video coding with multiple side information
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
Multichannel Correlation Model for Efficient Decoding in Wyner-Ziv Video Codec
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Distributed video coding: basics, main solutions and trends
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Adaptive correlation estimation for general Wyner-Ziv video coding
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Spatial non-stationary correlation noise modeling for Wyner-Ziv error resilience video coding
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Distributed video coding: trends and perspectives
Journal on Image and Video Processing - Special issue on distributed video coding
Compensating for motion estimation inaccuracies in DVC
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
Turbo code using adaptive puncturing for pixel domain distributed video coding
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
Low delay distributed video coding with refined side information
Image Communication
Distributed video coding with compressive measurements
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Journal of Visual Communication and Image Representation
Cross-band noise model refinement for transform domain Wyner-Ziv video coding
Image Communication
An iterative algorithm for efficient adaptive GOP size in transform domain wyner-ziv video coding
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part II
Proceedings of the 20th ACM international conference on Multimedia
Dictionary learning based reconstruction for distributed compressed video sensing
Journal of Visual Communication and Image Representation
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In recent years, practical Wyner-Ziv (WZ) video coding solutions have been proposed with promising results. Most of the solutions available in the literature model the correlation noise (CN) between the original frame and its estimation made at the decoder, which is the so-called side information (SI), by a given distribution whose relevant parameters are estimated using an offline process, assuming that the SI is available at the encoder or the originals are available at the decoder. The major goal of this paper is to propose a more realistic WZ video coding approach by performing online estimation of the CN model parameters at the decoder, for pixel and transform domain WZ video codecs. In this context, several new techniques are proposed based on metrics which explore the temporal correlation between frames with different levels of granularity. For pixel-domain WZ (PDWZ) video coding, three levels of granularity are proposed: frame, block, and pixel levels. For transform-domain WZ (TDWZ) video coding, DCT bands and coefficients are the two granularity levels proposed. The higher the estimation granularity is, the better the rate-distortion performance is since the deeper the adaptation of the decoding process is to the video statistical characteristics, which means that the pixel and coefficient levels are the best performing for PDWZ and TDWZ solutions, respectively.