Convexity of a set of subthreshold stimuli implies a peak detector

Convexity of a set of subthreshold stimuli implies a peak detector Convexity of a set of subthreshold stimuli implies a peak detector A. D. LOGVINENKO* School of Psychology, Queen's University, Belfast, BT9 5BP, UK Received 12 September 1994; revised 17 October 1995; accepted 17 April 1996 Abstract-It has been shown that for every model of detection (whether single- or multi-channel, with linear or non-linear channels, and whatever decision rule), provided that it predicts a convex set of subthreshold stimuli, there is a psychophysically equivalent peak detector made up of a collection of linear analysers followed by a maximum-output decision rule. In this paper, the equivalent peak detector representations of some widely accepted detection models are calculated. The calculations rest on a general technique for deriving, from a given model, a formula which specifies the analyser most sensitive to any given stimulus. 1. INTRODUCTION _ The detection of a pattern implies that an observer is able to discriminate a two- dimensional luminance distribution over the visual field l(a, /3) = l0[1 + cx(a, f3)] from a background consisting of homogeneous patch of light of the same spatial configuration and mean luminance (here lo is mean luminance; a and f3 are horizontal and vertical spatial coordinates measured in degrees of visual http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Spatial Vision (continued as Seeing & Perceiving from 2010) Brill

Convexity of a set of subthreshold stimuli implies a peak detector

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Publisher
BRILL
Copyright
© 1996 Koninklijke Brill NV, Leiden, The Netherlands
ISSN
0169-1015
eISSN
1568-5683
D.O.I.
10.1163/156856896X00088
Publisher site
See Article on Publisher Site

Abstract

Convexity of a set of subthreshold stimuli implies a peak detector A. D. LOGVINENKO* School of Psychology, Queen's University, Belfast, BT9 5BP, UK Received 12 September 1994; revised 17 October 1995; accepted 17 April 1996 Abstract-It has been shown that for every model of detection (whether single- or multi-channel, with linear or non-linear channels, and whatever decision rule), provided that it predicts a convex set of subthreshold stimuli, there is a psychophysically equivalent peak detector made up of a collection of linear analysers followed by a maximum-output decision rule. In this paper, the equivalent peak detector representations of some widely accepted detection models are calculated. The calculations rest on a general technique for deriving, from a given model, a formula which specifies the analyser most sensitive to any given stimulus. 1. INTRODUCTION _ The detection of a pattern implies that an observer is able to discriminate a two- dimensional luminance distribution over the visual field l(a, /3) = l0[1 + cx(a, f3)] from a background consisting of homogeneous patch of light of the same spatial configuration and mean luminance (here lo is mean luminance; a and f3 are horizontal and vertical spatial coordinates measured in degrees of visual

Journal

Spatial Vision (continued as Seeing & Perceiving from 2010)Brill

Published: Jan 1, 1996

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