Task-driven and flexible mean judgment for heterogeneous luminance ensembles
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Spatial averaging of luminances over a variegated region has been assumed in visual processes such as light adaptation, texture segmentation, and lightness scaling. Despite the importance of these processes, how mean brightness can be computed remains largely unknown. We investigated how accurately and precisely mean brightness can be compared for two briefly presented heterogeneous luminance arrays composed of different numbers of disks. The results demonstrated that mean brightness judgments can be made in a task-dependent and flexible fashion. Mean brightness judgments measured via the point of subjective equality (PSE) exhibited a consistent bias, suggesting that observers relied strongly on a subset of the disks (e.g., the highest- or lowest-luminance disks) in making their judgments. Moreover, the direction of the bias flexibly changed with the task requirements, even when the stimuli were completely the same. When asked to choose the brighter array, observers relied more on the highest-luminance disks. However, when asked to choose the darker array, observers relied more on the lowest-luminance disks. In contrast, when the task was the same, observers’ judgments were almost immune to substantial changes in apparent contrast caused by changing the background luminance. Despite the bias in PSE, the mean brightness judgments were precise. The just-noticeable differences measured for multiple disks were similar to or even smaller than those for single disks, which suggested a benefit of averaging. These findings implicated flexible weighted averaging; that is, mean brightness can be judged efficiently by flexibly relying more on a few items that are relevant to the task.
KeywordsEnsemble perception Summary statistics Averaging Brightness Lightness
This work was partly supported by Grants-in-Aid for Scientific Research from the Japan Society for the Promotion of Science to E.K. (Grant Nos. 26285162 and 25285197). We are grateful to Sang Chul Chong, Charlie Chubb, and an anonymous reviewer for their helpful comments and suggestions on earlier versions of the manuscript.
Open Practices Statement
The data and materials for all experiments are available upon request from the authors.
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