A Time-Frequency Domain Approach to Super-resolution
Date Issued
2009
Date
2009
Author(s)
Lee, Chia-Hung
Abstract
Aliasing in images occurs when an image is sampled at a too low sampling rate. Conventionally, we consider aliasing useless and cancel it with an anti-aliasing filter. However, this also destroyed the information. In fact, aliasing also conveys useful information about the high frequency content of the image, which is exploited in super-resolution applications. We use a set of input images of the same scene to extract such high frequency information and create a higher resolution aliasing-free image. Typically, there is a small shift between the different images, such that they contain slightly different information about the scene. uper-resolution image reconstruction can be formulated as a multichannel sampling problem with unknown offsets. This thesis concentrates on the computation of these offsets, as they are an essential prerequisite for an accurate high resolution reconstruction. A frequency domain approach based on Fourier transform is proposed by Vandewalle, Susstrunk, and Vetterli. The registration parameters between a pair of signals are computed using the aliasing-free part of the spectrum. However, the method cannot work for totally-aliased signals. In this thesis, we extend the concept to the time-frequency domain, based on Gabor transform. Theoretically, our algorithm will perform better, since the frequency domain approach is simply a special case of the time-frequency domain approach. The experiment results show that the performance indeed increases when dealing with real signals and images.
Subjects
Super-resolution
registration
aliasing
time-frequency
Gabor transform
Type
thesis
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