Prevalent theories of pattern vision postulate mechanisms selectively sensitive to spatial frequency and position but not to contrast. Decreased performance in the detection of visual stimuli was found when the observer was uncertain about the spatial frequency or spatial position of a patch of sinusoidal grating but not when he was uncertain about contrast. The uncertainty effects were consistent with multiple-band models in which the observer is able to monitor perfectly all relevant mechanisms. Performance deteriorates when the observer must monitor more mechanisms, because these mechanisms are noisy and give rise to false alarms. This consistency is further evidence that the spatial-frequency and spatial-position mechanisms are noisy, a conclusionpreviously suggested by the "probability summation" demonstrated in the thresholds for compound stimuli. Somewhat paradoxically, the Quick pooling model, which quantitatively accounts for the amount of probability summation in pattern thresholds, predicts no effects of uncertainty. It cannot, therefore, be strictly correct.Current theories of pattern vision assume the existence of mechanisms (often called channels) selectively sensitive to different spatial frequencies and also of mechanisms selectively sensitive to different spatial positions. A possible physiological substrate for a spatial-frequency channel is an array of neurons having receptive fields all of the same size and orientation but located at different positions within the visual field. A possible physiological substrate for a mechanism sensitive to a particular spatial position is the set of receptive fields located at that position. (See Graham, 1981, for a review.)A particular quantitative version of this theory has been extremely successful in predicting the thresholds for a wide variety of patterns (e.g., Bergen, Wilson, & Cowan, 1979;Graham, 1977;Graham, Robson, & Nachmias, 1978;Mostafavi & Sakrison, 1976;Quick, Mullins, & Reichert, 1978;Robson & Graham, 1981;Watson, 1982;. Although a name for this model has not become standard, we will call it the Quick pooling model since its current use in vision originates with Quick (1974) and it is much quicker to use than alternative models.The Quick pooling model, as derived from assumptions of independent variability in the responses of each of the multiple mechanisms, is the pure form of a high-threshold model in which the possibility of a false alarm in any mechanism is actually zero.