Wiener filtering of the COBE differential microwave radiometer data

We derive an optimal linear filter to suppress the noise from the COBE Differential Microwave Radiometer (DMR) sky maps for a given power spectrum. We then apply the filter to the first-year DMR data, after removing pixels within 20° of the Galactic plane from the data. We are able to identify particular hot and cold spots in the filtered maps at a level 2 to 3 times the noise level. We use the formalism of constrained realizations of Gaussian random fields to assess the uncertainty in the filtered sky maps. In addition to improving the signal-to-noise ratio of the map as a whole, these techniques allow us to recover some information about the cosmic microwave background anisotropy in the missing Galactic plane region. From these maps we are able to determine which hot and cold spots in the data are statistically significant, and which may have been produced by noise. In addition, the filtered maps can be used for comparison with other experiments on similar angular scales.