Do you have a link to share for more info on what exactly they're doing? (or even some raw images next to some deconvolved ones?)
Regarding SNR, I believe these images are being sent lossless (whereas the preliminary high-res images we're getting in a few weeks will be lossy for now). Presumably they have a good profile of their camera from before launch too, knowing that they'd have to do this. So I wouldn't be surprised if this analysis does turn out to be accurate. Let's hope!
The 3rd image in the original article compares the original and the deconvolved result.
The main idea is you want to invert a linear transformation (a matrix) which is given by the operation of your imaging system, i.e. a blurring operation. This linear transform often has a poor condition number, however - this means that you can't really invert it, or if you try to you end up with certain components of your signal that need huge amplification, which makes noise sensitivity a major issue.
One solution to this is to introduce a "prior" on your signal that represents your expectations about what the signal looks like, i.e. is it smooth, or does it have a few edges etc. Then you can better tolerate the inherent sensitivities. I'm not sure what priors they're using for this situation or if they're using any at all, so in the absence of such a description I'm taking the results with a grain of salt.
Do you have a link to share for more info on what exactly they're doing? (or even some raw images next to some deconvolved ones?)
Regarding SNR, I believe these images are being sent lossless (whereas the preliminary high-res images we're getting in a few weeks will be lossy for now). Presumably they have a good profile of their camera from before launch too, knowing that they'd have to do this. So I wouldn't be surprised if this analysis does turn out to be accurate. Let's hope!