Albert J. Ahumada

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Nonlinear contributions to pattern classification by humans are analyzed by using previously obtained data on discrimination between aligned lines and offset lines. We show that the optimal linear model (which had been identified by correlating the noise added to the presented patterns with the observerÕs response) can be rejected even when the parameters(More)
Our previous experiments with additive and multiplicative transparent text on textured backgrounds show that readability can be more accurately predicted by adjusting the contrast with a contrast-gain-like divisive factor that includes the background RMS contrast. However, the factor performed poorly at predicting readability differences on two different(More)
The aim of the ColorFest is to extend the original ModelFest ( experiments to build a spatio-chromatic standard observer for the detection of static coloured images. The two major issues that need to be addressed are (1) the contrast sensitivity functions for the three chromatic mechanisms and (2) how the output of(More)