Abstract #3404
An Approach to Improve the Effectiveness of Wavelet and Contourlet Compressed Sensing Reconstruction
Paniz Adipour 1 and Michael R. Smith 1,2
1
Electrical and Computer Engineering,
University of Calgary, Calgary, Alberta, Canada,
2
Radiology,
University of Calgary, Calgary, Alberta, Canada
Truncation artifacts appear in DFT reconstructions
through discontinuities across the ends of the data set
which mathematically is cyclic in
k
-space.
A suggestion indicates that similar position dependent
distortions will be present in CS reconstructions which
repeatedly use the DFT. A comparison is made between
standard Wavelet and Contourlet CS reconstructions and
proposed high k-space extrapolation enabled (
Hi-KEE
)
variants of these approaches. The CS-Contourlet
outperforms the common CS-Wavelet in providing a better
sparse representation of contour-shaped objects and
detailed textures. The
Hi-KEE
-CS-Contourlet
is shown to outperform the CS-Contourlet by providing a
better position independent resolution solution.
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