Imaging Fourier-transform spectrometers (IFTS) have the potential to measure spatial variations in plume temperature and density. However, the turbulent flow yields rapid, stochastic fluctuations in radiance during interferometric measurements which corrupt corresponding spectra. A novel, statistics-based method of interpreting a time-sequence of interferograms collected from a stochastic blackbody source is presented which enables good estimation of the underlying temperature distribution. It is shown that the median (and various other quantiles) interferograms afford unbiased spectral estimates of temperature upon Fourier transformation, in contrast to temperature estimates based on spectra obtained from mean interferograms. This method is then applied to IFTS data (200×64 pixels at 1cm-1 resolution) of a turbulent exhaust plume from a small turbojet engine. Spatial maps of brightness temperature and estimates of turbulence-induced temperature distribution are presented.