We address the restoration of noisy and blurred images that are scanned from photographic paper. In this case, we need to consider the nonilnearities introduced by both the photographic film and the paper. To this effect, we first transform the measured reflection density of the photographic paper into the scene exposure domain in which a linear convolutional relationship between the original scene and the degraded image can be established. As a result of this transformation, any additive noise in the reflection density domain becomes multiplicative in the scene exposure domain. We
then propose a linear filter for deconvolution in the exposure domain in the presence of multiplicative observation noise. Experiments with actual noisy and blurred images scanned from photographic paper indicate that the nonlinear sensor characteristics must be incorporated into image restoration to obtain satisfactory results. We also compare the quality of the restoration results when the same blurred image is scanned from the photographic negative (film) and the print (paper) obtained from this negative.