Abstract:
:We propose a method for restoring the underlying true signal in noisy functional images. The Nadaraya-Watson (NW) estimator described in, e.g., [1] is a classical nonparametric estimator for this problem. Since the true scene in many applications contains abrupt changes between pixels of different types, a modification of the NW estimator is needed. In the data we study, the characteristics of each pixel are given as a function of time. This means that a curve of data points is observed at each pixel. Utilizing this time information, the NW weights can be modified to obtain a weighted average over pixels with the same true value. Theoretical results showing the estimator's properties are developed. Several parameters play an important role for the restoration result. Practical guidelines are given for how these parameters can be selected. Finally, we demonstrate how the method can be successfully applied both to artificial data and Magnetic Resonance Images.
journal_name
IEEE Trans Med Imagingjournal_title
IEEE transactions on medical imagingauthors
Godtliebsen F,Chu CK,Sørbye SH,Torheim Gdoi
10.1109/42.906423subject
Has Abstractpub_date
2001-01-01 00:00:00pages
36-44issue
1eissn
0278-0062issn
1558-254Xjournal_volume
20pub_type
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