The goal of this study was to compare two scatter compensation methods for myocardial perfusion SPECT imaging, namely the effective scatter source estimation (ESSE) and the dual energy window (DEW) methods. A population of 12 male Dynamic Cardiac Torso (DNCAT) anatomies were used. Low-noise projections were simulated for each organ of each anatomy using Monte Carlo simulation with scatter, attenuation and detector response modelling. The organ projections were then combined to form 36 sets of projections for each anatomy using randomly sampled activity ratios from a clinically realistic distribution. Poisson noise was then added to create clinically realistic projections with different noise levels for each phantom. Reconstruction was performed using OS-EM with attenuation and detector response compensation with the addition of no, ESSE or DEW scatter compensation. For EESE scatter compensation, the scatter was modelled for each iteration in the forward projector, and for DEW scatter compensation, the estimated scatter projections were obtained from a 5 keV wide energy window immediately below the primary photopeak window, scaled with a factor of 2.8 and filtered with a Gaussian filter. A channelized Hotelling observer was used to model human defect detection, and the area under the receiver operating characteristics curve (AUC) was used as a figure of merit We found that optimal cutoff frequency of the Gaussian filter applied to DEW estimate was 8 pixels FWHM. The AUC values for ESSE, DEW and no scatter compensation were 0.850, 0.843 and 0.839 respectively. The p value for ESSE vs. DEW was 0.0630, ESSE vs. no scatter compensation method was 0.0466 and DEW vs. no scatter compensation method was 0.1649. Both scatter compensation methods outperformed no scatter compensation and ESSE outperformed DEW, though only the difference between ESSE and no compensation was statistically significant at a confidence level of 5%.