The submicroscan interpolation image-processing technique is analyzed to determine the effects of additive noise on the quality of the output imagery. Both temporal and fixed-pattern spatial noise are evaluated assuming a white Gaussian noise model. Closed-form solutions for the power spectral density of the output noise are derived for both one- and two-dimensional submicroscanning. It is found that temporal noise degrades the output imagery and determines the minimum usable submicroscan image shift. For the case of fixed-pattern noise, submicroscan interpolation causes a spectral redistribution of the noise power spectrum that tends to improve image quality.