Power spectrum model of visual masking: simulations and empirical data

In the study of the spatial characteristics of the visual channels, the power spectrum model of visual masking is one of the most widely used. When the task is to detect a signal masked by visual noise, this classical model assumes that the signal and the noise are previously processed by a bank of linear channels and that the power of the signal at threshold is proportional to the power of the noise passing through the visual channel that mediates detection. The model also assumes that this visual channel will have the highest ratio of signal power to noise power at its output. According to this, there are masking conditions where the highest signal-to-noise ratio (SNR) occurs in a channel centered in a spatial frequency different from the spatial frequency of the signal (off-frequency looking). Under these conditions the channel mediating detection could vary with the type of noise used in the masking experiment and this could affect the estimation of the shape and the bandwidth of the visual channels. It is generally believed that notched noise, white noise and double bandpass noise prevent off-frequency looking, and high-pass, low-pass and bandpass noises can promote it independently of the channel's shape. In this study, by means of a procedure that finds the channel that maximizes the SNR at its output, we performed numerical simulations using the power spectrum model to study the characteristics of masking caused by six types of one-dimensional noise (white, high-pass, low-pass, bandpass, notched, and double bandpass) for two types of channel's shape (symmetric and asymmetric). Our simulations confirm that (1) high-pass, low-pass, and bandpass noises do not prevent the off-frequency looking, (2) white noise satisfactorily prevents the off-frequency looking independently of the shape and bandwidth of the visual channel, and interestingly we proved for the first time that (3) notched and double bandpass noises prevent off-frequency looking only when the noise cutoffs around the spatial frequency of the signal match the shape of the visual channel (symmetric or asymmetric) involved in the detection. In order to test the explanatory power of the model with empirical data, we performed six visual masking experiments. We show that this model, with only two free parameters, fits the empirical masking data with high precision. Finally, we provide equations of the power spectrum model for six masking noises used in the simulations and in the experiments.

Visual Discrimination Increase by Yellow Filters in Retinitis Pigmentosa

PURPOSE: The objective of this study was to evaluate, by halometry and under low illumination conditions, the effects of short-wavelength light absorbance filters on visual discrimination capacity in retinitis pigmentosa patients. METHODS: This was an observational, prospective, analytic, and transversal study on 109 eyes of 57 retinitis pigmentosa patients with visual acuity better than 1.25 logMAR. Visual disturbance index (VDI) was determined using the software Halo 1.0, with and without the interposition of filters which absorb (totally or partially) short-wavelength light between 380 and 500 nm. RESULTS: A statistically significant reduction in the VDI values determined using filters which absorb short-wavelength light was observed (p < 0.0001). The established VDIs in patients with VA logMAR <0.4 were 0.30 ± 0.05 (95% CI, 0.26–0.36) for the lens alone, 0.20 ± 0.04 (95% CI, 0.16–0.24) with the filter that completely absorbs wavelengths shorter than 450 nm, and 0.24 ± 0.04 (95% CI, 0.20–0.28) with the filter that partially absorbs wavelengths shorter than 450 nm, which implies a 20 to 33% visual discrimination capacity increase. In addition, a decrease of VDI in at least one eye was observed in more than 90% of patients when using a filter. CONCLUSIONS: Short-wavelength light absorbance filters increase visual discrimination capacity under low illumination conditions in retinitis pigmentosa patients. Use of such filters constitutes a suitable method to improve visual quality related to intraocular light visual disturbances under low illumination conditions in this group of patients. © 2016 American Academy of Optometry