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We fit model spectral energy distributions to each pixel in 67 nearby(<z>=0.0057) galaxies using broadband photometry from the Sloan Digital SkySurvey and GALEX. For each galaxy, we compare the stellar mass derived bysumming the mass of each pixel to that found from fitting the entire galaxytreated as an unresolved point source. We find that, while the pixel-by-pixeland unresolved masses of galaxies with low specific star formation rates (suchas ellipticals and lenticulars) are in rough agreement, the unresolved massestimate for star-forming galaxies is systematically lower then the measurementfrom spatially-resolved photometry. The discrepancy is strongly correlated withsSFR, with the highest sSFRs in our sample having masses underestimated by 25%(0.12 dex) when treated as point sources. We found a simple relation tostatistically correct mass estimates derived from unresolved broad-band SEDfitting to the resolved mass estimates: m_{resolved} =m_{unresolved}/(-0.057log(sSFR) + 0.34) where sSFR is in units of yr^{-1}. Westudy the effect of varying spatial resolution by degrading the imageresolution of the largest images and find a sharp decrease in thepixel-by-pixel mass estimate at a physical scale of approximately 3 kpc, whichis comparable to spiral arm widths. The effects we observe are consistent withthe "outshining" idea which posits that the youngest stellar populations maskmore massive, older -- and thus fainter -- stellar populations. Although thepresence of strong dust lanes can also lead to a drastic difference betweenresolved and unresolved mass estimates (up to 45% or 0.3 dex) for anyindividual galaxy, we found that resolving dust does not affect mass estimateson average. The strong correlation between mass discrepancy and sSFR is thusmost likely due to the outshining systematic bias.

Missing Stellar Mass in SED Fitting: Spatially Unresolved Photometry can Underestimate Galaxy Masses