Simple color-difference formulae and pictorial images have
traditionally been used to estimate the visual impact of color errors
introduced by image-reproduction processes. But the limited gamut of RGB
cameras constrains such analyses, particularly of natural scenes. The
purpose of this work was to estimate visual sensitivity to color errors
introduced deliberately into pictures synthesized from hyperspectral
images of natural scenes without gamut constraints and to compare
discrimination thresholds expressed in CIELAB and S-CIELAB color spaces.
From each original image, a set of approximate images with variable color
errors were generated and displayed on a calibrated RGB color monitor. The
threshold for perceptibility of the errors was determined in a
paired-comparison experiment. In agreement with previous studies, it was
found that discrimination between original and approximate images needed
on average a CIELAB color difference
ΔEab* of about 2.2. Although a large
variation of performance across the nine images tested was found when
errors were expressed in CIELAB units, little variation was obtained when
they were expressed in S-CIELAB units.