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header for SPIE use Masking in color images
 

Summary: header for SPIE use
Masking in color images
Albert J. Ahumada, Jr. *a , William K. Krebs **b
a NASA Ames Research Center; b FAA
ABSTRACT
Masking of color targets was measured for fixed pattern noises made of all additive combinations of white/black, red/green,
and blue/yellow noise. Results are compared with the predictions of a cone­contrast­based masking model with and without
cross­channel masking. The model without cross­channel masking performed very well.
Keywords: color vision, target detection, image discrimination, vision models, image quality metrics, visual masking,
contrast energy, color channels, color representations
1. INTRODUCTION
This study is part of a project to develop image discrimination models that can predict the detectability of targets in color
images. Image discrimination models take as input two images and predict the number of just­noticeable differences (JNDs)
between the images. If one image is a background image and the other image has the identical background plus a target
image, the model predicts the detectability of the target in the background.
Previous work with luminance targets in complex imagery has shown that target detectability is strongly influenced by
variations in background contrast. 1­3 A simple model for masking that was used with some success was to adjust the
detectability prediction by a contrast gain control factor based on the RMS visible contrast. 1, 4­5 The theoretical goal here was
to develop a color version of this simple model with three color channels and estimate parameters representing the masking
effects within and between these channels. The experimental goal is to measure the masking of targets by fixed­pattern

  

Source: Ahumada Jr., Al - Vision Science and Technology Group, Human Factors Research and Technology Division, NASA Ames Research Center

 

Collections: Engineering