Cite as:
May K A, Georgeson M A, 2003, "Perceiving edge blur: Gaussian-derivative filtering and a rectifying nonlinearity" Perception 32 ECVP Abstract Supplement

Perceiving edge blur: Gaussian-derivative filtering and a rectifying nonlinearity

K A May, M A Georgeson

A template model for edge perception successfully predicts perceived blur for a wide variety of edge profiles (Georgeson, 2001 Journal of Vision 1 438a). The model differentiates the luminance profile, half-wave rectifies this first derivative, and then differentiates again to create the 'signature' of the edge. The spatial scale of the signature is evaluated by filtering with a set of Gaussian derivative operators whose response measures the correlation between the signature and the operator kernel. These kernels thus act as templates for the edge signature, and the position and scale of the best-fitting template indicate the position and blur of the edge. The rectifier accounts for a range of effects on perceived blur (Barbieri-Hesse and Georgeson, 2002 Perception 31 Supplement, 54). It also predicts that a blurred edge will look sharper when a luminance gradient of opposite sign is added to it. Experiment 1 used blur-matching to reveal a perceived sharpening that was close to the predicted amount. The model just described predicts that perceived blur will be independent of contrast, but experiment 2 showed that blurred edges appeared sharper at lower contrasts. This effect can be explained by subtracting a threshold value from the gradient profile before rectifying. At low contrasts, more of the gradient profile falls below threshold and its effective spatial scale shrinks in size, leading to perceived sharpening. As well as explaining the effect of contrast on blur, the threshold improves the model's account of the added-ramp effect (experiment 1).

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