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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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