2026-09-19T14:25:21Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/898582022-01-13T07:54:01Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Jae S. Lim.
Fuller, Megan M. (Megan Marie)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2014-09-19T19:37:53Z
2014-09-19T19:37:53Z
2014
2014
http://hdl.handle.net/1721.1/89858
890150793
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
14
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 85-86).
A common problem that arises in image processing is that of performing inverse filtering on an image that has been blurred. Methods for doing this have been developed, but require fairly accurate knowledge of the magnitude of the Fourier transform of the blurring function and are sensitive to noise in the blurred image. It is known that a typical image is defined completely by its region of support and a sufficient number of samples of the phase of its Fourier transform. We will investigate a new method of deblurring images based only on phase data. It will be shown that this method is much more robust in the presence of noise than existing methods and that, because no magnitude information is required, it is also more robust to an incorrect guess of the blurring filter. Methods of finding the region of support of the image will also be explored.
by Megan M. Fuller.
S.M.
86 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Inverse filtering by signal reconstruction from phase
Thesis
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