  Despite their widespread use in cell biology, fluorescence lifetime imaging
microscopy (FLIM) data-sets are challenging to analyse. This is because, in
each spatial position, there is typically a superposition of multiple
fluorescent components. Here, we present a data analysis method making the most
out of the information in the available photon budget, while being fast and
unbiased. The method, called uFLIM, determines spatial distributions and
temporal dynamics of multiple fluorescent components with no prior knowledge.
It goes significantly beyond current approaches which either assume the
functional dependence of the dynamics, e.g. an exponential decay, or require
dynamics to be known. Its efficient non-negative matrix factorization algorithm
allows for real-time data processing. We show that uFLIM is capable to
disentangle the spatial distribution and spectral properties of 5 fluorescing
probes, from only two excitation and detection channels and a photon budget of
100 detected photons per pixel. By adapting the method to data exhibiting
F\"orster resonant energy transfer (FRET), we retrieve the spatial and transfer
rate distribution of the bound species, without constrains on donor and
acceptor dynamics. The deployment of this powerful unsupervised method allows
to extract the maximum information from FLIM-FRET data.
