One of the most challenging research topics in the field of target detection in electro-optical images is the relationship between image content and human detection performance. We propose two target structure similarity (TSSIM) metrics to describe global image clutter. Via a simple mathematical formula, the TSSIM clutter metrics and their combinations with different local target-to-background contrasts, which are loosely referred to as signal-to-clutter ratios (SCRs), are used to predict human detection performance. Other clutter measures and their combinations with the contrast ones are also considered for comparison. The degrees of correlation between target detection probabilities and various clutter metrics, as well as the SCR models, are presented. Experiment results show that the TSSIM measures are more suitable for quantifying electro-optical clutter than other clutter measures compared. And the SCR metric, which combines the root-sum-of-squares local contrast and a TSSIM clutter metric, generates the best predictive capabilities for the experimental detection probabilities.