Correlation between slightly misaligned images
As suggested by Dan Boschen, I maximized the Spearman's correlation coefficient over all possible “small” translations – where small is less than 15 pixels in L1-distance – of the rendered PDF page images. The results were underwhelming, but I suppose this method would work much better if the camera images weren't optically distorted.

In the figure below, Pearson's r between the left and middle images is 0.789 and Spearman's r is 0.479. Pearson's r between the left and right images is 0.8008 and Spearman's r is 0.5094.



As suggested by Marcus Müller, I used a feature detector (ORB, not SURF) to find keypoints in the images. Rather than directly use the feature descriptors for matching, I used them to find a homography that registers the two images.

In the figure below, Pearson's r between the left and middle images is 0.6244 and Spearman's r is 0.4921. Pearson's r between the left and right images is 0.0213 and Spearman's r is 0.036. For my test case, this works remarkably well.