Sparse-Prony FRI signal reconstruction

Finite rate of innovation (FRI) approach is used for sampling and reconstruction of a class of non-bandlimited continuous signals having a finite number of free parameters. Traditionally, Prony and matrix-pencil methods are proposed to reconstruct FRI signals from the discrete samples. However, thes...

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Bibliographic Details
Published in:Signal, image and video processing image and video processing, 2023-10, Vol.17 (7), p.3443-3449
Main Authors: Reddy, P. Sudhakar, Raghavendra, B. S., Narasimhadhan, A. V.
Format: Article
Language:English
Subjects:
Computer Imaging
Computer Science
Image Processing and Computer Vision
Multimedia Information Systems
Original Paper
Pattern Recognition and Graphics
Polynomials
Signal reconstruction
Signal to noise ratio
Signal,Image and Speech Processing
Vision
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Summary:Finite rate of innovation (FRI) approach is used for sampling and reconstruction of a class of non-bandlimited continuous signals having a finite number of free parameters. Traditionally, Prony and matrix-pencil methods are proposed to reconstruct FRI signals from the discrete samples. However, these methods tend to break down at a certain signal-to-noise ratio (SNR). In this paper, we propose sparsity-based annihilating filter, refer it as sparse-Prony, which avoids polynomial root-finding. In the noiseless scenario, the proposed method is able to recover perfectly the original signal. Simulation results for the noisy scenario demonstrate significant improvement in the performance in terms of MSE over the traditional FRI methods, especially in the breakdown SNR.
ISSN:1863-1703
1863-1711
DOI:10.1007/s11760-023-02566-3