ah I think I misunderstood your question the first time…
This seems relatively straightforward if you want to represent the image with 625 (25x25) neurons, you can simply flatten the image out into a vector and pass this 625x1 vector into your 625 neurons…
but if instead you want to represent the image as the correlations between two sets of 25 neurons (50 neurons total). This seems more complicated.
making up a solution from scratch you could do something like generate input currents with the desired correlation properties (perhaps out of some orthogonal signal basis set) then feed these into your 25 + 25 neurons. Then the image might be “read out” of the neuron from the observed cross-correlation matrix of the network, is that what you’re looking for?