Hi I dived somewhat into deconvolution of systems which can be described as:
$s(t) = o(t) * h(t) + n(t)$
where $s$ is my measured 1D time resolved signal, $o$ is the original signal $h$ is the kernel or PSF pf my system, which is convolved with the original signal (with $*$ beeing the convolution operator), $n$ as sample-function for $1/f^\alpha$ noise ($\alpha > 0$).
For all I know there are several methods to deconvolve for an estimate of o. When choosing the correct method, the consideration of the noise is important. E.g. I should use the wiener deconvolution for systems with white noise, lucy-richardson for possion noise.
Which method should I use for pink noise (given the fact that there are several other (read: deeper mathematical) aspect which should be taken into account)?
On a side note: any recomendations for Papers/Books on this topic (Deconvolution of systems as described)? Thanks in advance!
Edit: For the system I know an estimate of the kernel function $h$ and I can make blank meassurements to estimate the nature of the nois sample function (it ssemst to be white noise for small freqencies and pink noise for higher freqencies).