Classification Image Weights and Internal Noise Level Estimation  (2000)

For the case of linear discrimination of two stimuli in white Gaussian noise in the presence of internal noise, a method is described for estimating linear classification weights from the sum of noise images segregated by stimulus and response. The recommended method for combining the two response image for the same stimulus is to difference the average images. Weights are derived for combining images over stimuli and observers. Methods for estimating the level of internal noise are described, especially for the case of repeated presentations of the same noise sample. Simple tests for particular hypotheses about the weights are shown based on observer agreement with a noiseless version of the hypothesis.

+ Watson, Andrew

+ Ahumada, Albert

+ Vision Science and Technology

detection, discrimination, vision

Journal of Vision, 2(1), 121-131. http://www.journalofvision.org/2/1/8/

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