Inverse filtering by signal reconstruction from phase
Name
890150793-MIT.pdf
Description
Full printable version
Size
7.64 MB
Format
Adobe PDF
Checksum (MD5)
a67d4e9ee7f7cbf2fcd341407ab65176
Author(s)
Fuller, Megan M. (Megan Marie)
Advisor(s)
Jae S. Lim.
Date Issued
2014
Publisher
Massachusetts Institute of Technology
Abstract
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.
Description
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).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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