Digitized images: what type of grey scale should one use?

The standard deviation of luminance as a metric for contrast in random-dot images

Michelson's contrast, C, is an excellent metric for contrast in images with periodic luminance profiles, such as gratings, but is not suitable for images consisting of isolated stimulus elements, eg single bars; other metrics have been devised for such stimuli. But what metric should be used for random-dot images such as are commonly used in stereograms and kinematograms? Previously the standard deviation (SD) of the luminances (equivalent to the root mean square, RMS, of the amplitudes) has been taken as a measure of contrast, but on little more than intuitive grounds. The validity of this speculative usage is tested. Experiments are described in which a wide range of random-dot images of various compositions was used and the adapting power of these images measured. This was taken as an index of their visual effectiveness. The contrast and contrast-reducing effects of the stimuli were expressed in terms of six candidate metrics, including SD, to discover which would give the most lawful description of the experimental data. The usefulness and generality of the SD measure were confirmed. The effects of mean luminance were also measured and a general expression that would take them into account was derived. Finally, on the basis of computational modelling in which spatial filters with properties approximating those of retinal ganglion cells were used, a possible theoretical account for the success of the SD metric is offered.

Modelling visual detection: luminance response non-linearity and internal noise

Two experiments that investigate the effect of various display factors on the detectability of a thin line signal in random visual noise are described. Three statistical decision models are described, together with their ability to account for the results. The first is an "ideal detector" model, the second an "energy integrator" model, and the third a model based upon the operation of retinal ganglion cells which incorporates a gain control mechanism. The ideal detector model fails to give a good account of human performance, whereas the other two models provide a good fit to the data. The digital Laplacian with gain control model has the slight advantage over the energy integrating model in being able to account for a small superiority in the detection of dark as opposed to bright signals. Finally, both models require the inclusion of an estimate of the internal noise of the human visual system to account for the pattern of performance observed under changing conditions of display contrast.

White's effect: a dual mechanism

White (1979) has described a phenomenon in which grey bars replacing segments of the white phase of a square-wave grating appear darker than identical grey bars replacing segments of the black phase of the grating. We have investigated the properties of this effect with a view to discovering the underlying mechanisms. Four experiments are reported which reveal the effects of the heights and widths of both the flank and coaxial inducing bars upon the brightness of the grey bars. The results show that two processes, one the local corner effect, and one a spatially extensive process (possibly involving filters with elongated end-zones) operate to produce the effect. The implications of the findings for models of brightness perception are discussed and suggestions are made for further experiments.