The vast majority of previous work in noise reduction for visual media has assumed uncorrelated, white, noise sources. In practice this is almost always violated by real media. Film grain noise is never white, and this paper highlights that the same applies to almost all consumer video content. We therefore present an algorithm for measuring the spatial and temporal spectral density of noise in archived video content, be it consumer digital camera or film orginated. As an example of how this information can be used for video denoising, the spectral density is then used for spatio-temporal noise reduction in the Fourier frequency domain. Results show improved performance for noise reduction in an easily pipelined system.