Il Yong Chun1,
Thomas Talavage1, 2
1School
of Electrical and Computer Engineering, Purdue University, West Lafayette,
IN, United States; 2Weldon School of Biomedical Engineering,
Purdue University, West Lafayette, IN, United States
We propose two pre-computation-allowable and non-iterative MAP SENSE reconstruction algorithms based on 1) a Gaussian Random Field (GRF) with non-zero mean and 2) a Huber-Markov Random Field (HMRF) with non-zero mean. Simulation results show that the non-iterative HMRF MAP regularization technique is more effective for edge preservation and residual aliasing artifact reduction than non-iterative GRF MAP and Tikhonov-type regularization methods.