I’m not sure, if you mean the Hermitian adjoint, but if so I assume you would like to inverse the convolution?
If so, then note that inverse filtering is often not a good idea, if it doesn’t account for the additional error signal in the input:
(f * g) + e = h

If you know the type of noise (e.g. Gaussian) you could use a Wiener deconvolution.
For a general use case you could use the FFT and reverse the (noise free) convolution via:
F = H / G

and apply the inverse FFT again.