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tokens: scale of PSF, which causes correlation of the fluctuations in adjacent pixels; (e) estimating the “residual variance” from contaminating sources remaining in the masked image and subtracting this variance from the power spectrum amplitude to obtain the corrected SBF magnitude ; (f) adopting a value for from either an empirical or theoretical SBF calibration (generally based on galaxy color) to obtain the distance modulus, . For this NGVS SBF analysis, we adopted the sky background estimates and galaxy isophotal models described by Ferrarese et al. ( 2012 ). The large-scale residuals, still present in the frame after subtracting the galaxy model, were removed using the background map obtained with SExtractor (Bertin Arnouts 1996 ) adopting a mesh size ≈10 times the FWHM (Tonry et al. 1990 ; Cantiello et al. 2005 ). We refer to the image with the sky, galaxy model, and large-scale residuals all subtracted as the residual frame. The photometry of the external sources (stars, background galaxies, and GCs) was done by running SExtractor on the residual frame after masking saturated stars, very extended galaxies, and other large features that could be problematic for SExtractor. We used an input weight image that included the galaxy photometric noise as well as additional variance caused by the SBF (for details, see Jordán et al. 2004 ; Cantiello et al. 2005 ) to avoid detecting the fluctuations as objects themselves. The SExtractor MAG_AUTO measurements include roughly 90% of the light from faint sources; the aperture corrections for these magnitudes were obtained from a number of isolated sources in each frame using a curve-of-growth analysis out to large radii (Cantiello et al. 2009 , 2011b ). The cutouts of the NGVS images used for the analysis are wide on each side; on such scales the PSF variation is small enough that the typical rms scatter is ∼0.01 mag for the aperture corrections. 9 9 For galaxies close to MegaPrime image tile edges, where the PSF or the image quality might be rapidly changing on spatially small scales, we limited our aperture corrections, PSF selection, and SBF analysis to the regions with the best image quality. Once the catalog of sources had been derived, the next step was to fit the luminosity function of the sources, which was necessary in order to estimate the amount of contamination from unmasked faint sources in the residual frame. We fitted a source magnitude distribution to a model, including a combination of the GCLF and a power-law background galaxy luminosity function (examples are shown in Figure 1 , discussed below). As noted above, bright stars and the most extended sources had been masked and were therefore not present in the catalog. At these high Galactic latitudes, the surface density of fainter stars is small compared the GCs in the vicinity of bright galaxies. The best fit to the combined GCLF and galaxy luminosity function was used to derive the background fluctuation correction term, P r , as