A ASED NEW INTE~OLATION METHOD FOR MEDICAL IMAGES
Cliff X. Wang, Pete Santago · 1996
interpolation is very important in many medical imaging applications. The problems of interpolating low resolution medical images are approached in this paper as an optimization problem. The objective function is derived from Bayesian Maximum-a-posteriori (MAP) probability density, which effectively combines the measured low resolution image data with apriori knowledge of the image property. Solution to the optimizution problem produces a zoomed image which resembles the measured low resolution image, but hus noise smoothed and blur corrected. Keyword: Image interpolation, Maximum a posteriori probability, Mean field annealing