A fast wavelet-based algorithm for signal recovery from partial Fourier domain information

Signal reconstruction from the measurements of its Fourier transform magnitude remains an important and difficult problem that occurs in different areas in signal processing. Among all the approaches developed to solve this problem, the iterative transform algorithms are currently the most efficient...

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Veröffentlicht in:IEEE transactions on circuits and systems. 2, Analog and digital signal processing Analog and digital signal processing, 1998-08, Vol.45 (8), p.1134-1136
Hauptverfasser: Rabadi, W.A., Myler, H.R.
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container_title IEEE transactions on circuits and systems. 2, Analog and digital signal processing
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creator Rabadi, W.A.
Myler, H.R.
description Signal reconstruction from the measurements of its Fourier transform magnitude remains an important and difficult problem that occurs in different areas in signal processing. Among all the approaches developed to solve this problem, the iterative transform algorithms are currently the most efficient. However, these algorithms suffer from major drawbacks such as stagnation, slow convergence, and high computational cost that limit their practical application. In this brief, we introduce a wavelet adaptation of the general iterative algorithm where the problem is decomposed into different resolution levels and the image is reconstructed following a coarse-to-fine strategy. We show that the proposed approach can significantly improve the performance of the existing algorithms while dramatically reducing their computational complexity.
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subjects Area measurement
Computational efficiency
Convergence
Fourier transforms
Image reconstruction
Image resolution
Iterative algorithms
Iterative methods
Signal processing algorithms
Signal reconstruction
title A fast wavelet-based algorithm for signal recovery from partial Fourier domain information
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