Reconstruction of high-resolution image frames from a sequence of low-resolution and compressed observations

C. Andrew Segall; Rafael Molina; Aggelos K. Katsaggelos; Javier Mateos

doi:10.1109/ICASSP.2002.5744948

Reconstruction of high-resolution image frames from a sequence of low-resolution and compressed observations

C. Andrew Segall, Rafael Molina, Aggelos K. Katsaggelos, Javier Mateos

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

A framework for recovering high-resolution information from a sequence of sub-sampled and compressed observations is presented. Compression schemes that describe a video sequence through a combination of motion vectors and transform coefficients are the focus (e.g. the MPEG and ITU family of standards), and we consider the influence of both the motion vectors and transform coefficients within the reconstruction algorithm. A Bayesian approach is utilized to incorporate the information, and results show a discernable improvement in resolution, as compared to standard interpolation methods.

Original language	English (US)
Pages (from-to)	1701-1704
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2
DOIs	https://doi.org/10.1109/ICASSP.2002.5744948
State	Published - 2002

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

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10.1109/ICASSP.2002.5744948

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abstract = "A framework for recovering high-resolution information from a sequence of sub-sampled and compressed observations is presented. Compression schemes that describe a video sequence through a combination of motion vectors and transform coefficients are the focus (e.g. the MPEG and ITU family of standards), and we consider the influence of both the motion vectors and transform coefficients within the reconstruction algorithm. A Bayesian approach is utilized to incorporate the information, and results show a discernable improvement in resolution, as compared to standard interpolation methods.",

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Reconstruction of high-resolution image frames from a sequence of low-resolution and compressed observations. / Segall, C. Andrew; Molina, Rafael; Katsaggelos, Aggelos K. et al.
In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Vol. 2, 2002, p. 1701-1704.

Research output: Contribution to journal › Article › peer-review

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T1 - Reconstruction of high-resolution image frames from a sequence of low-resolution and compressed observations

AU - Segall, C. Andrew

AU - Molina, Rafael

AU - Katsaggelos, Aggelos K.

AU - Mateos, Javier

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AB - A framework for recovering high-resolution information from a sequence of sub-sampled and compressed observations is presented. Compression schemes that describe a video sequence through a combination of motion vectors and transform coefficients are the focus (e.g. the MPEG and ITU family of standards), and we consider the influence of both the motion vectors and transform coefficients within the reconstruction algorithm. A Bayesian approach is utilized to incorporate the information, and results show a discernable improvement in resolution, as compared to standard interpolation methods.

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Reconstruction of high-resolution image frames from a sequence of low-resolution and compressed observations

Abstract

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