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 |
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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. |
doi_str_mv | 10.1109/82.718825 |
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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.</description><subject>Area measurement</subject><subject>Computational efficiency</subject><subject>Convergence</subject><subject>Fourier transforms</subject><subject>Image reconstruction</subject><subject>Image resolution</subject><subject>Iterative algorithms</subject><subject>Iterative methods</subject><subject>Signal processing algorithms</subject><subject>Signal reconstruction</subject><issn>1057-7130</issn><issn>1558-125X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1998</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEFLAzEQhYMoWKsHr55yEjxsnWTNJjmWYlUoeFEQL0t2M6mR3U1Nti39965s8TSPme89mEfINYMZY6DvFZ9JphQXJ2TChFAZ4-LjdNAgZCZZDufkIqVvAFBMqwn5nFNnUk_3ZocN9lllElpqmnWIvv9qqQuRJr_uTEMj1mGH8UBdDC3dmNj7YbsM2-gxUhta4zvqu8HRmt6H7pKcOdMkvDrOKXlfPr4tnrPV69PLYr7Kap7LPuOVMMKZXAO31tWDgkLmwCEXDpyWFkHjAy-0lmgE14iygOFXa1VVVYLlU3I75m5i-Nli6svWpxqbxnQYtqnkUuRas2IA70awjiGliK7cRN-aeCgZlH_tlYqXY3sDezOyHhH_uePxF5pGaxk</recordid><startdate>19980801</startdate><enddate>19980801</enddate><creator>Rabadi, W.A.</creator><creator>Myler, H.R.</creator><general>IEEE</general><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>19980801</creationdate><title>A fast wavelet-based algorithm for signal recovery from partial Fourier domain information</title><author>Rabadi, W.A. ; Myler, H.R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c237t-2b5a5fa3902ddfcfa3067302035f0f97de09e426997ea529ee760110dd8bbb513</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1998</creationdate><topic>Area measurement</topic><topic>Computational efficiency</topic><topic>Convergence</topic><topic>Fourier transforms</topic><topic>Image reconstruction</topic><topic>Image resolution</topic><topic>Iterative algorithms</topic><topic>Iterative methods</topic><topic>Signal processing algorithms</topic><topic>Signal reconstruction</topic><toplevel>online_resources</toplevel><creatorcontrib>Rabadi, W.A.</creatorcontrib><creatorcontrib>Myler, H.R.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on circuits and systems. 2, Analog and digital signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Rabadi, W.A.</au><au>Myler, H.R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A fast wavelet-based algorithm for signal recovery from partial Fourier domain information</atitle><jtitle>IEEE transactions on circuits and systems. 2, Analog and digital signal processing</jtitle><stitle>T-CAS2</stitle><date>1998-08-01</date><risdate>1998</risdate><volume>45</volume><issue>8</issue><spage>1134</spage><epage>1136</epage><pages>1134-1136</pages><issn>1057-7130</issn><eissn>1558-125X</eissn><coden>ICSPE5</coden><abstract>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.</abstract><pub>IEEE</pub><doi>10.1109/82.718825</doi><tpages>3</tpages></addata></record> |
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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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