Improving Color Discrimination in Color Vision Deficiency Using MPEG–21

Abstract

Purpose: : Color vision deficiency (CVD) affects roughly one in twenty people throughout the world. There is a remarkable lack of treatment options available for the correction of impaired color vision. The effect of digital modification of color hue and saturation on the color discrimination ability was investigated in people with red–green CVD.

Methods: : A color adaptation program was developed based on spectral cone sensitivities of the human eye and spectral emission characteristics of a display monitor. Color hue and saturation shifts were determined according to shifts of peak sensitivity and shape obtained by Smith and Pokorny anomalous cone models. 37 subjects with color vision deficiency were screened with pseudoisochromatic plates and CVD type was determined with an anomaloscope. Color discrimination ability was then tested for each eye using a computerized Farnsworth–Munsell 100 (cFM–100) hue test. Color hue and saturation of cFM–100 tiles were digitally modified at five different degrees according to the color adaptation program, after which subjects had their color discrimination abilities tested again. Digital color adaptation was applied to a colored image of the letter "A" and two Ishihara plates in a separate group of 8 subjects.

Results: : Mean cFM–100 error scores were significantly improved from the baseline score of 156.9 to the post–adaptation score of 140.6 at the 0.5 adaptation degree (p=0.004), 134.3 at the 0.7 adaptation degree (p<0.0001), and 133.2 at the 0.9 adaptation degree (p<0.0001). 63% (22) of subjects were able to see the letter "A" better and 75% (6) gained the ability to discern one of the two Ishihara images following color image adaptation.

Conclusions: : Digital color adaptation appears to improve color discrimination ability and may assist in the perception of color in images for people with red–green CVD.

Keywords: color vision