High Order Image Reconstruction from Fourier Data
Abstract:
Fourier spectral data is often the source of image information. For example, magnetic resonance imaging (MRI) and synthetic aperture radar (SAR) sensors measure the values of the Fourier coefficients of an image. The FFT provides an efficient way to reconstruct the image. Since the underlying image often contains edges, the reconstruction is polluted by the Gibbs ringing artifact. Although this is somewhat alleviated by filtering, the ``blurring'' at the internal boundaries of the image can lead to difficulties in segmentation and misdiagnosis. This talk discusses how to determine the internal boundaries and how to reconstruct the image without blurring or the Gibbs ringing effects. As a result, image segmentation is much more accurate. Some examples from MRI are included.
Applied Mathematics Seminar