title: Effective contrast of colored stimuli in the mesopic range: a metric for perceived contrast based on achromatic luminance contrast.
abstract: Little is known about how color signals and cone- and rod-based luminance signals contribute to perceived contrast in the mesopic range. In this study the perceived contrast of colored, mesopic stimuli was matched with that of spatially equivalent achromatic stimuli. The objective was to develop a metric for perceived contrast in the mesopic range in terms of an equivalent achromatic luminance contrast, referred to here as effective contrast. Stimulus photopic luminance contrast, scotopic luminance contrast, and chromatic difference from the background all contributed to effective contrast over the mid-mesopic range, but their contributions were not independent and varied markedly with background luminance. Surprisingly, color made a significant contribution to effective contrast from 10 to approximately 0.003 cd m(-2). A model describing this relationship is introduced (R2 = 0.89) and compared with predictions of mesopic luminance contrast obtained from a number of models proposed as systems of mesopic photometry.
authors.affiliation: Applied Vision Research Centre, City University, Northampton Square, London EC1 V 0HB, UK. h.c.walkey@city.ac.uk
authors.forename: Helen C
authors.initials: HC
authors.lastname: Walkey
authors.forename: John L
authors.initials: JL
authors.lastname: Barbur
authors.forename: J Alister
authors.initials: JA
authors.lastname: Harlow
authors.forename: Antony
authors.initials: A
authors.lastname: Hurden
authors.forename: Ian R
authors.initials: IR
authors.lastname: Moorhead
authors.forename: Julie A F
authors.initials: JA
authors.lastname: Taylor
mesh_terms: D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D003118:Color Perception / Q000502:physiology*; D003124:Colorimetry / Q000379:methods / Q000592:standards; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods* / Q000592:standards; D016247:Information Storage and Retrieval / Q000379:methods*; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods* / Q000592:standards; D012015:Reference Standards; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013647:Task Performance and Analysis