The Hotelling Observer (HO),1 along with its channelized variants,2 has been proposed for image quality evaluation in x-ray CT.3,4 In this work, we investigate HO performance for a detection task in parallel-beam FBP as a function of two image-domain sampling parameters, namely pixel size and field-of-view. These two parameters are of central importance in adapting HO methods to use in CT, since the large number of pixels in a single image makes direct computation of HO performance for a full image infeasible in most cases. Reduction of the number of image pixels and/or restriction of the image to a region-of-interest (ROI) has the potential to make direct computation of HO statistics feasible in CT, provided that the signal and noise properties lead to redundant information in some regions of the image. For small signals, we hypothesize that reduction of image pixel size and enlargement of the image field-of-view are approximately equivalent means of gaining additional information relevant to a detection task. The rationale for this hypothesis is that the backprojection operation in FBP introduces long range correlations so that, for small signals, the reconstructed signal outside of a small ROI is not linearly independent of the signal within the ROI. In this work, we perform a preliminary investigation of this hypothesis by sweeping these two sampling parameters and computing HO performance for a signal detection task.