The time-shift technique is a well-documented technique for the size and velocity measurement of individual drops passing through one or two tightly focused laser beams. It is a counting technique, nominally applicable for pure liquid drops, but with potential to also characterize drops with embedded particles or drops containing a second dispersed phase. In the present study a novel approach to signal processing is introduced in which the signal detection and validation phase is eliminated. This extends the capabilities of the time-shift technique in two manners. For one, size and velocity estimates are made possible for drops exhibiting very poor signal structure or signal-to-noise ratio. Such signals are commonly expected when measuring complex drops, either drops with embedded nano/micro-particles (dispersions) or emulsions. Second, the size and velocity distributions are estimated not by processing of signals from individual drops (single realization counting technique), but from a large ensemble of drop signals, improving both computational speed and reducing the influence of outliers in final statistics. These capabilities are achieved without sacrificing accuracy of mean and variance estimates of size and velocity of drop ensembles. To demonstrate the advantages of this new approach, measurements of a paint spray are presented, processed using both standard processing routines and the new approach. Limitations concerning the application of this new approach are discussed in detail.