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Lauren F. V. Scharff, Albert J. Ahumada; Identification of filtered letters in filtered noise. Journal of Vision 2002;2(7):281. doi: 10.1167/2.7.281.
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Several researchers have investigated the effects of filtering letters and/or added noise on letter identification (e.g. Legge, Pelli, Rubin & Schleske, 1985 (letters filtered but no noise added); Parish & Sperling, 1991 (noise filter matched letter filter); Solomon & Pelli, 1994 (noise filtered but letters unfiltered)). This study compares the combined effects of high and low pass filtering on both letters and noise. Letters (Arial font, 24 pt) that were unfiltered, high- or low-band pass filtered (sharp cut off frequency of approximately 4 cycles per capital letter height) were presented in unfiltered, high- or low-band pass filtered noise (9 combinations). Three participants made 26-alternative, forced-choice responses for each of the 9 conditions (counterbalanced, blocked presentation) for both upper and lower case letters. For each condition, three replications of 30 trial threshold estimations were run, in which letter contrast was adjusted by a Quest algorithm. Averaged thresholds showed that for a given noise, unfiltered letters (the sum of the high- and low-pass letters) led to better recognition than either component filtered letter alone. However estimates for summation indexes in the different noises were strikingly different. In the wide band noise, summation was between linear and Euclidean. In high-pass noise, the summation was quite linear. But, for low-pass noise, there was no summation. Adding the low-pass letter component did not improve performance; high-pass letters in low-pass noise led to better performance than unfiltered letters in low-pass noise. The results qualitatively support a moveable single filter model where the filter band was moved most in the low-pass noise and least in the high-pass noise.
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