We investigate a Wiener fusion method to optimally combine multiple estimates
for the problem of image deblurring given a known blur and a corpus of sharper training images.
Nearest-neighbor estimation of high frequency information from training images is fused
with a standard Wiener deconvolution estimate. Results show an improvement in sharpness
and decreased artifacts compared to either the standard Wiener filter or the nearest-neighbor