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RI | Publications | Variable Window Gabor Filters and Their Use in Focus and Correspondence
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Variable Window Gabor Filters and Their Use in Focus and Correspondence
Y. Xiong and S. Shafer
tech. report CMU-RI-TR-94-06, Robotics Institute, Carnegie Mellon University, March, 1994.
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| Abstract |
More and more low level vision algorithms are being carried out in the spatial frequency domain, using Gabor filters. There are two basic problems concerned with Gabor filterings we will address in this paper. One is the window size problem, in which we will adopt a set of 2D variable window Gabor filters, and compare its performance with those of fixed window filters. We will show that the variable window scheme is more adaptive to image contents, while fixed window schemes may suffer either large errors or instabilities when image contents are changed. The other problem we will address is the stability of amplitude and phase information resulting from convolving the filters with images. We will extend Fleet's 1D phase stability analysis to 2D phase and amplitude stability analysis based upon the assumption of local resemblance of filter outputs to a single sinusoid. Applications on focus quality measurement and 2D correspondence are described, and the results demonstrate improvements of performance by detecting unstable information using the criterion developed.
| Notes |
Grant ID: NAGW 1175
Associated center: VASC
Associated lab/group: Calibrated Imaging Lab
Associated project: Depth From Focus and Defocus
Number of pages: 22
| Text Reference |
Y. Xiong and S. Shafer, Variable Window Gabor Filters and Their Use in Focus and Correspondence, tech. report CMU-RI-TR-94-06, Robotics Institute, Carnegie Mellon University, March, 1994.
| BibTeX Reference |
@techreport{Xiong_1994_326,
author = "Yalin Xiong and Steven Shafer",
title = "Variable Window Gabor Filters and Their Use in Focus and Correspondence",
institution = "Robotics Institute, Carnegie Mellon University",
month = "March",
year = "1994",
number = "CMU-RI-TR-94-06",
address = "Pittsburgh, PA"
}