Parameter-Free Compressed Sensing Reconstruction Using Statistical Non-Local Self-Similarity Filtering

Mariya Doneva¹, Tim Nielsen¹, Peter Brnert¹

In this work, we present a CS reconstruction based on statistical non-local self-similarity filtering (STAINLeSS). The method provides improved image quality compared to wavelet based CS reconstruction and does not require any parameter adjustments. All the parameters are automatically determined by the noise estimation in the receive channels obtained from a standard noise measurement.