Different definitions of the signal-to-noise ratio (SNR) are being used as metrics to describe the image quality of remote sensing systems. It is usually not clear which SNR definition is being used and what the image quality of the system is when an SNR value is quoted. This paper looks at several SNR metrics used in the remote sensing community. Image simulations of the Kodak Space Remote Sensing Camera, Model 1000, were produced at different signal levels to give insight into the image quality that corresponds with the different SNR metric values. The change in image quality of each simulation at different signal levels is also quantified using the National Imagery Interpretability Rating Scale (NIIRS) and related to the SNR metrics to better understand the relationship between the metric and image interpretability. An analysis shows that the loss in image interpretability, measured as ΔNIIRS, can be modeled as a linear relationship with the noise-equivalent change in reflection (NEΔρ). This relationship is used to predict the values that the various SNR metrics must exceed to prevent a loss in the interpretability of the image from the noise. © 2001 Society of Photo-Optical Instrumentation Engineers.