This paper presents a method which allows for a reduced portion of a particle image velocimetry (PIV) image to be analysed, without introducing numerical artefacts near the edges of the reduced region. Based on conﬁdence intervals of statistics of interest, such a region can be determined automatically depending on user-imposed conﬁdence requirements, allowing for already satisfactorily converged regions of the ﬁeld of view to be neglected in further analysis, oﬀering signiﬁcant computational beneﬁts. Temporal ﬂuctuations of the ﬂow are unavoidable even for very steady ﬂows, and the magnitude of such ﬂuctuations will naturally vary over the domain. Moreover, the non-linear modulation eﬀects of the cross-correlation operator exacerbate the perceived temporal ﬂuctuations in regions of strong spatial displacement gradients. It follows, therefore, that steady, uniform, ﬂow regions will require fewer contributing images than their less steady, spatially ﬂuctuating, counterparts within the same ﬁeld of view, and hence the further analysis of image pairs may be solely driven by small, isolated, non-converged regions. In this paper, a methodology is presented which allows these non-converged regions to be identiﬁed and subsequently analysed in isolation from the rest of the image, while ensuring that such localised analysis is not adversely aﬀected by the reduced analysis region, i.e. does not introduce boundary eﬀects, thus accelerating the analysis procedure considerably. Via experimental analysis, it is shown that under typical conditions a 44% reduction in the required number of correlations for an ensemble solution is achieved, compared to conventional image processing routines while maintaining a speciﬁed level of conﬁdence over the domain.