Multi-channel reconstruction of video sequences from low-resolution and compressed observations. Luis, D A., Rafael, M., & Aggelos, K K. 2003. doi abstract bibtex A framework for recovering high-resolution video sequences from sub-sampled and compressed observations is presented. Compression schemes that describe a video sequence through a combination of motion vectors and transform coefficients, e.g. the MPEG and ITU family of standards, are the focus of this paper. A multichannel Bayesian approach is used to incorporate both the motion vectors and transform coefficients in it. Results show a discernable improvement in resolution in the whole sequence, as compared to standard interpolation methods. © Springer-Verlag Berlin Heidelberg 2003.
@misc{Luis2003,
abstract = {A framework for recovering high-resolution video sequences from sub-sampled and compressed observations is presented. Compression schemes that describe a video sequence through a combination of motion vectors and transform coefficients, e.g. the MPEG and ITU family of standards, are the focus of this paper. A multichannel Bayesian approach is used to incorporate both the motion vectors and transform coefficients in it. Results show a discernable improvement in resolution in the whole sequence, as compared to standard interpolation methods. {\textcopyright} Springer-Verlag Berlin Heidelberg 2003.},
author = {Luis, D Alvarez and Rafael, Molina and Aggelos, K Katsaggelos},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-540-24586-5_5},
pages = {46--53},
title = {{Multi-channel reconstruction of video sequences from low-resolution and compressed observations}},
volume = {2905},
year = {2003}
}
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