The Standard Deviation of Luminance as a Metric for Contrast in Random-Dot Images

Abstract

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.

Detection of temporal order of noise-like luminance functions

“…The averages" < >" in Equation Al are temporal. We use a root mean square (RMS) definition for contrast, which is very reasonable for our noise-like stimuli (Moulden, Kingdom, & Gatley, 1990). Note that Equation A 1 holds independently of the clock frequency fthat determines the presentation duration b of individual bits in the m-sequence: b = 11f This is at variance with the percept of our observers: perceived contrast decreases with decreasing bit duration b (i.e., increasing/).…”

Distributed and Dynamic Neural Encoding of Multiple Motion Directions of Transparently Moving Stimuli in Cortical Area MT

“…The luminance levels of the dots and the background were 15.3 and 1.9 cd/m 2 , respectively, giving rise to a Michelson contrast of 0.78. The SD of the luminance intensity of the random-dot pattern was 1.95 cd/m 2 , which reflects the root mean square contrast (Moulden et al, 1990;Peli, 1990). The bidirectional stimuli contained two overlapping random-dot patterns translating in different directions.…”

The role of spatial frequency information for ERP components sensitive to faces and emotional facial expression

“…All face and house stimuli were equated for mean luminance and were normalized for root mean square (RMS) contrast subsequent to filtering in Matlab. RMS contrast has been shown to be a reasonable metric for perceived contrast in random noise patterns [51] and natural images [10]. This was implemented by calculating the total RMS energy of each luminance-equated image, and then dividing the luminance at each pixel in the image by this value.…”