Abstract #4877

A New Approach to Incorporate Image Prior Estimate in Compressed Sensing

Bing Wu^1,2, Philip Bones¹, Richard Watts³, Rick Millane¹

¹Electrical and computer engineering, University of Canterbury, Christchurch, Canterbury, New Zealand; ²Brain Imaging and Analysis Center, School of Medicine, Duke University, Durham, NC, United States; ³Physics and Astronomy, University of Canterbury, New Zealand

The success level of compressed sensing (CS) reconstruction is fundamentally limited by the sparsity of the underlying image. A data sorting process can be incorporated in the CS recovery to improve the sparsity of the underlying image based on the knowledge of an image prior estimate. We here show that performing a data sorting effectively incorporates the image prior estimate in the CS reconstruction.