Motion sharpening and contrast: gain control precedes compressive non-linearity?

Blurred edges appear sharper in motion than when they are stationary. We (Vision Research 38 (1998) 2108) have previously shown how such distortions in perceived edge blur may be accounted for by a model which assumes that luminance contrast is encoded by a local contrast transducer whose response becomes progressively more compressive as speed increases. If the form of the transducer is fixed (independent of contrast) for a given speed, then a strong prediction of the model is that motion sharpening should increase with increasing contrast. We measured the sharpening of periodic patterns over a large range of contrasts, blur widths and speeds. The results indicate that whilst sharpening increases with speed it is practically invariant with contrast. The contrast invariance of motion sharpening is not explained by an early, static compressive non-linearity alone. However, several alternative explanations are also inconsistent with these results. We show that if a dynamic contrast gain control precedes the static non-linear transducer then motion sharpening, its speed dependence, and its invariance with contrast, can be predicted with reasonable accuracy.

Motion, flash, and flicker: a unified spatiotemporal model of perceived edge sharpening.

Blurred edges appear sharper in motion than when they are stationary. We proposed a model of this motion sharpening that invokes a local, nonlinear contrast transducer function (Hammett et al, 1998 Vision Research 38 2099-2108). Response saturation in the transducer compresses or 'clips' the input spatial waveform, rendering the edges as sharper. To explain the increasing distortion of drifting edges at higher speeds, the degree of nonlinearity must increase with speed or temporal frequency. A dynamic contrast gain control before the transducer can account for both the speed dependence and approximate contrast invariance of motion sharpening (Hammett et al, 2003 Vision Research, in press). We show here that this model also predicts perceived sharpening of briefly flashed and flickering edges, and we show that the model can account fairly well for experimental data from all three modes of presentation (motion, flash, and flicker). At moderate durations and lower temporal frequencies the gain control attenuates the input signal, thus protecting it from later compression by the transducer. The gain control is somewhat sluggish, and so it suffers both a slow onset, and loss of power at high temporal frequencies. Consequently, brief presentations and high temporal frequencies of drift and flicker are less protected from distortion, and show greater perceptual sharpening.