As an editor, what measures can I implement to prevent image/photo manipulation? There's been a case of alleged data manipulation in a recent Nano Letters paper (initial report here; now-retracted paper):

    

You can surely make your own opinion on whether the images have been digitally modified, given the above snapshots (look for gray rectangles around the rods); I was careful to write “alleged” because the paper’s PI threatened legal action against the blogger who reported the issue.



Now, this case lead to a large number of comments here and there about whose responsibility it was to catch this issue (reviewers or editor). I tend to agree that the reviewer should probably have caught it, but this lead me to wonder:

As editor of a scholarly journal, what measures can I implement to prevent image/photo manipulation? And what about data manipulation? Organic Letters has made the news two months ago when they hired a in-house data analyst. Is that the way to go? Are there other measures one could take to reduce the threat of image and data manipulation?
I think a search term for this type of manipulation detection is image forensics.  Matthias Kirchner: Notes on Digital Image Forensics and
Counter-Forensics may be a starting point. 

What can you do?

I think a first step is to communicate clearly what image manipulations* are acceptable and which are not:


is it acceptable to adjust brightness and contrast?
correct unequal illumination?
whitelight correction based not on a whitelight measurement but on parts of the image?
digital sharpening or other enhancement filters?
where's the border between an inset picture and a fraudulent manipulation?


and so on.

Who should detect this?

I agree that the reviewer should have commented and asked about the pictures above, however my experience as reviewer is that I often get pictures in ridiculously low resolution (I comment on that). I'm not sure, but I think that the publishers may ask for high resolution pictures when they spot such problems in the production process. However, that would mean that the reviewers may not have seen the actual picture that is used for printing. 



* manipulation in the data analysis sense: calculations that change the information content (e.g. enhance contrast), and cannot be easily undone (as opposed to a transformation where the back transformation is easily possible, e.g. rotation), not in the sense of fraud.