A new robust method for two-dimensional inverse filtering
In this paper, we present a novel method for inverse filtering a two dimensional (2-D) signal using phase-based processing techniques. A 2-D sequence can be represented by a sufficient number of samples of the phase of its Fourier transform and its region of support. This is exploited to perform dec...
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SPIE
2016
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Online Access: | http://hdl.handle.net/1721.1/100816 https://orcid.org/0000-0002-7028-8439 https://orcid.org/0000-0002-9170-784X |
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author | Lim, Jae S. Fuller, Megan Marie |
author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Lim, Jae S. Fuller, Megan Marie |
author_sort | Lim, Jae S. |
collection | MIT |
description | In this paper, we present a novel method for inverse filtering a two dimensional (2-D) signal using phase-based processing techniques. A 2-D sequence can be represented by a sufficient number of samples of the phase of its Fourier transform and its region of support. This is exploited to perform deconvolution. We examine the effects of additive noise and incomplete knowledge of the point spread function on the performance of this deconvolution method and compare it with other 2-D deconvolution methods. The problem of finding the region of support will also be briefly addressed. Finally, an application example will be presented. |
first_indexed | 2024-09-23T11:50:34Z |
format | Article |
id | mit-1721.1/100816 |
institution | Massachusetts Institute of Technology |
language | en_US |
last_indexed | 2024-09-23T11:50:34Z |
publishDate | 2016 |
publisher | SPIE |
record_format | dspace |
spelling | mit-1721.1/1008162022-10-01T06:25:22Z A new robust method for two-dimensional inverse filtering Lim, Jae S. Fuller, Megan Marie Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Research Laboratory of Electronics Fuller, Megan Marie Lim, Jae S. In this paper, we present a novel method for inverse filtering a two dimensional (2-D) signal using phase-based processing techniques. A 2-D sequence can be represented by a sufficient number of samples of the phase of its Fourier transform and its region of support. This is exploited to perform deconvolution. We examine the effects of additive noise and incomplete knowledge of the point spread function on the performance of this deconvolution method and compare it with other 2-D deconvolution methods. The problem of finding the region of support will also be briefly addressed. Finally, an application example will be presented. 2016-01-13T18:39:21Z 2016-01-13T18:39:21Z 2015-03 Article http://purl.org/eprint/type/ConferencePaper 0277-786X http://hdl.handle.net/1721.1/100816 Fuller, Megan M., and Jae S. Lim. “A New Robust Method for Two-Dimensional Inverse Filtering.” Edited by Amir Said, Onur G. Guleryuz, and Robert L. Stevenson. Visual Information Processing and Communication VI (March 4, 2015). © 2015 Society of Photo-Optical Instrumentation Engineers (SPIE) https://orcid.org/0000-0002-7028-8439 https://orcid.org/0000-0002-9170-784X en_US http://dx.doi.org/10.1117/12.2078070 Proceedings of SPIE--the International Society for Optical Engineering Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf SPIE SPIE |
spellingShingle | Lim, Jae S. Fuller, Megan Marie A new robust method for two-dimensional inverse filtering |
title | A new robust method for two-dimensional inverse filtering |
title_full | A new robust method for two-dimensional inverse filtering |
title_fullStr | A new robust method for two-dimensional inverse filtering |
title_full_unstemmed | A new robust method for two-dimensional inverse filtering |
title_short | A new robust method for two-dimensional inverse filtering |
title_sort | new robust method for two dimensional inverse filtering |
url | http://hdl.handle.net/1721.1/100816 https://orcid.org/0000-0002-7028-8439 https://orcid.org/0000-0002-9170-784X |
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