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Running Gaussian reference-based reconstruction for video compressed sensing

Authors: W. Hotrakool, C. Abhayaratne

Appeared in: Proceedings of 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2014

Abstract: Our recent work has shown that quality of compressed sensing reconstruction can be improved immensely by minimising the error between the signal and a correlated reference, as opposed to the conventional l1-minimisation of the data measurements. This paper introduces a method for online estimating suitable references for video sequences using the running Gaussian average. The proposed method can provide robustness to video content changes as well as reconstruction noise. The experimental results demonstrate the performance of this method to be superior to those of the state-of-the-art l1-min methods. The results are comparable to the lossless reference reconstruction approach.

DOI: 10.1109/ICASSP.2014.6853949

Find it on: IEEEXplore, ResearchGate

Copy BiBTeX:

@inproceedings{6853949,
author={Hotrakool, Wattanit and Abhayaratne, Charith},
booktitle={2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title={Running Gaussian reference-based reconstruction for video compressed sensing},
year={2014},
month={May},
pages={2001-2005}}

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