Multiple description coding using pairwise correlating transforms
By Yao Wang, Michael T. Orchard, V. Vaishampayan, Amy R. Reibman. IEEE Transactions on Image Processing, 2001
383 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/7c3c0ec66efdf62176756bf500d1d8f0a321c000
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Yao Wang
- Shunan Lin
- Martin Reisslein
- Amy R. Reibman
- K. Müller
- Vivek K Goyal
- Jörn Ostermann
- Guoliang Xue
In Signal Processing
- Yao Wang
- Shunan Lin
- Martin Reisslein
- Amy R. Reibman
- K. Müller
- Vivek K Goyal
- Jörn Ostermann
- A. Smolic
Citations in the corpus
- Multiple description coding: compression meets the network (2001, background): “Better results obtained with more general correlating transforms appear in [110].”
- Multiple Description Coding for Video Delivery (2005, methodology): “We call them MDTC-FMC and MDTC-PMC, with the suffixes indicating full mismatch coding and partial mismatch coding, respectively.”
- A survey of multimedia streaming in wireless sensor networks (2008, methodology): “is obtained using the Redundancy Rate Distortion (RRD) curve [52].”
- Coding Algorithms for 3DTV—A Survey (2007, background): “transform domain, and the transform coefficients are ordered by their variances, a subsequent pairwise correlating transform (PCT) has been suggested with a purpose to couple and correlate them into pairs [113].”