Image enhancement has, in general, a substantial effect on human detection performance of targets embedded in infrared images. However, different enhancement techniques, as well as different surrounding conditions, cause this effect to vary. In this paper, we analyze the effect of several histogram modeling enhancement methods on human detection performance, according to specially designed psychophysical experiment results. We also present, using the Analysis of Variance (ANOVA) statistical tool, how this effect varies according to different surrounding conditions, and whether the effect is statistically significant. A quantitative empirical criterion for enhancement efficiency is introduced and used to show how histogram modeling enhancement can considerably improve poor detection performance associated with natural images, provided that the applied enhancement method does not change drastically the natural image Pixel Distribution Function (PDF). On the other hand, if the criterion is not achieved, histogram modeling enhancement has negligible influence.