> This in the absence of noise (which is a *big* assumption) and ignoring 
> image boundaries you could compute (non-blind) deconvolution by using FFT 
> on the image and the kernel and dividing, which is a pretty efficient 
> operation.

The problem is the convoluted version you have "the photo" is not made of 
complex numbers (which it would be if you did the convolution yourself). 
You need this in order to do the deconvolution, otherwise you don't have 
enough information.  See my 1D example in the other post.

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