I've got a set of scans of an object (human body) from different angles, which are being combined to reconstruct a 2D-representation. The raw measurements (blue plot below) contain a fair amount of spikes, which I reduce by using a median filter (result in green plot below). Afterwards I filter the result with a FIR lowpass filter to further remove noise (red figure below).
This produces at least visually appealing results, though I don't know if it is the best possible solution. Are there any pitfalls, when chaining median and linear filtering?
Another problem is, the samples are not evenly spaced. The distribution of samples seems to be somewhat $1/x$-ish, though I don't take this into account when smoothing the data.
Can this be ignored for simple smoothing? If yes, why? If no, how can I factor in the irregular spacing?