You are not currently logged in.
Access your personal account or get JSTOR access through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Incorporation of Spatial Information in Bayesian Image Reconstruction: The Maximum Residual Likelihood Criterion
R. K. Piña and R. C. Puetter
Publications of the Astronomical Society of the Pacific
Vol. 104, No. 681 (1992 November), pp. 1096-1103
Published by: Astronomical Society of the Pacific
Stable URL: http://www.jstor.org/stable/40679969
Page Count: 8
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
We have developed a new figure of merit, a "maximum-residual-likelihood" (MRL) statistic, for the goodness of fit for Bayesian image restoration which explicitly incorporates spatial information. The MRL constraint provides a natural means of incorporating the prior knowledge that the residuals contain no spatial structure through the autocorrelation function of the residuals. We demonstrate that this statistic follows a x² distribution and that forcing this statistic to have its most probable value leads to a restored image whose residuals are consistent with the noise model. Our numerical experiments suggest that image restoration using the MRL statistic alone (without an "image prior," e. g., an entropy function) is numerically robust and produces results which are independent of the initial guess for the restored image. However, we caution that using the MRL statistic without an image prior can result in overresolution in low signal-to-noise portions of the image.
Publications of the Astronomical Society of the Pacific © 1992 The University of Chicago Press