An approach for robust segmentation of images from arbitrary blurred and noisy Fourier data
Datum konání: 06.01.2012
Přednášející: Rosemary Renaut
Odpovědná osoba: Šroubek
I will review approaches for detecting edges from Fourier data. Application to cases where the data is noisy, blurred, or partially missing, requires use of a regularization term, and accompanying regularization parameter. Our analysis focuses on validation through robustness with respect to correctly classifying edge data. Note that in this method, segmentation is achieved without reconstruction of the underlying image.