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Vision science has identified a number of factors that affect detection threshold for spatial targets in backgrounds. Typically, simple stimuli are used to allow precise experimental control and rigorous hypothesis testing. However, an ultimate goal of vision science is to understand performance under natural conditions, where multiple factors are varying simultaneously in complex ways. We propose a direct experimental approach for identifying and quantifying the factors that affect detection performance in natural scenes. First, we obtain a large representative collection of calibrated natural images. Next, we divide the images up into millions of background patches and sort them into narrow bins along dimensions of interest. For example, in the present study each bin represents a particular (narrow range of) mean luminance, contrast, and spatial correlation of the background to a given target. Next, we measure …