Number of discernible colors for color-deficient observers estimated from the MacAdam limits

How the orientation of the color gamut of natural scenes influences color discrimination in red-green dichromacy

In natural scenes, visual discrimination of colored surfaces by individuals with X-linked dichromacy is known to be only a little poorer than in normal trichromacy. This surprising result may be related to the properties of the colors of these scenes, like the shape and orientation of the color gamut, uneven frequency, and a considerable variation in lightness. It is unclear, however, how much each of these factors contributes to the small impairment in discrimination, in particular, what is the contribution of the orientation of the gamut. We measured the discrimination of colors from natural scenes by six normal trichromats and six dichromats. Colors were drawn either from the original color gamut of the scenes or from gamut-rotated versions of the scenes. Pairs of colors were randomly drawn from hyperspectral images of one rural and one urban environment and presented on a screen. As expected, dichromats were only a little poorer than normal trichromats at discrimination but the disadvantage varied systematically with the orientation of the color gamut by a factor of about three with a minimum around a yellow-green axis. Dichromats also took longer to respond, and the response times were modulated with the orientation of the color gamut in a similar way as the loss in discrimination. For the scenes tested here, these results imply an important impact of the orientation of the gamut on discrimination. They also indicate that the predominantly yellow-blue orientation of the gamut of natural scene might not be optimal for discrimination in dichromacy.

Discrimination of natural colors in anomalous trichromacy and the effects of EnChroma and Vino filters

It is still unclear how well anomalous trichromats discriminate natural colors and whether commercial spectral filters improve performance in these conditions. We show that anomalous trichromats have good color discrimination with colors drawn from natural environments. It is only about 14% poorer, on average, than normal trichromats in our sample of thirteen anomalous trichromats. No measurable effect of the filters on discrimination was found, even after 8 hours of continuous use. Computations of cone and post-receptoral signals show only a modest increase in medium-to-long-wavelength difference signals, which may explain the absent effect of the filters.

The colors of natural scenes benefit dichromats

Dichromacy impairs color vision and impoverishes the discrimination of surface colors in natural scenes. Computational estimates based on hyperspectral imaging data from natural scenes suggest that dichromats can discriminate only about 10% of the colors discriminated by normal trichromats. These estimates, however, assume that the colors are equally frequent. Yet, pairs of colors confused by dichromats may be rare and thus have small impact on overall perceived chromatic diversity. This study estimated, empirically, how much dichromats are disadvantaged in discriminating surface colors drawn from natural scenes. The stimulus for the experiment was a scene made of real three-dimensional objects painted with matte white paint and illuminated by a spectrally tunable light source. In each trial the observers saw the scene illuminated by two spectra in two successive time intervals and had to indicate whether the colors perceived in the objects in the two intervals were the same or different. The spectra were drawn randomly from hyperspectral data of natural scenes and therefore represented natural spectral statistics. Four normal trichromats and four dichromats carried out the experiment. It was found that the number of pairs that could be discriminated by dichromats was almost 70% of those discriminated by normal trichromats, a proportion much higher than anticipated from estimates of discernible colors. Moreover, data from model simulations show that normal trichromats and dichromats use lightness differences for discrimination in about 40% and 50% of the discriminable pairs, respectively. Together these results suggest that the color distributions of natural scenes benefit the color vision of dichromats.

Robust colour constancy in red-green dichromats

Colour discrimination has been widely studied in red-green (R-G) dichromats but the extent to which their colour constancy is affected remains unclear. This work estimated the extent of colour constancy for four normal trichromatic observers and seven R-G dichromats when viewing natural scenes under simulated daylight illuminants. Hyperspectral imaging data from natural scenes were used to generate the stimuli on a calibrated CRT display. In experiment 1, observers viewed a reference scene illuminated by daylight with a correlated colour temperature (CCT) of 6700K; observers then viewed sequentially two versions of the same scene, one illuminated by either a higher or lower CCT (condition 1, pure CCT change with constant luminance) or a higher or lower average luminance (condition 2, pure luminance change with a constant CCT). The observers' task was to identify the version of the scene that looked different from the reference scene. Thresholds for detecting a pure CCT change or a pure luminance change were estimated, and it was found that those for R-G dichromats were marginally higher than for normal trichromats regarding CCT. In experiment 2, observers viewed sequentially a reference scene and a comparison scene with a CCT change or a luminance change above threshold for each observer. The observers' task was to identify whether or not the change was an intensity change. No significant differences were found between the responses of normal trichromats and dichromats. These data suggest robust colour constancy mechanisms along daylight locus in R-G dichromacy.

The Gold Standard Paradox in Digital Image Analysis: Manual Versus Automated Scoring as Ground Truth

CONTEXT

- Novel therapeutics often target complex cellular mechanisms. Increasingly, quantitative methods like digital tissue image analysis (tIA) are required to evaluate correspondingly complex biomarkers to elucidate subtle phenotypes that can inform treatment decisions with these targeted therapies. These tIA systems need a gold standard, or reference method, to establish analytical validity. Conventional, subjective histopathologic scores assigned by an experienced pathologist are the gold standard in anatomic pathology and are an attractive reference method. The pathologist's score can establish the ground truth to assess a tIA solution's analytical performance. The paradox of this validation strategy, however, is that tIA is often used to assist pathologists to score complex biomarkers because it is more objective and reproducible than manual evaluation alone by overcoming known biases in a human's visual evaluation of tissue, and because it can generate endpoints that cannot be generated by a human observer.

OBJECTIVE

- To discuss common visual and cognitive traps known in traditional pathology-based scoring paradigms that may impact characterization of tIA-assisted scoring accuracy, sensitivity, and specificity.

DATA SOURCES

- This manuscript reviews the current literature from the past decades available for traditional subjective pathology scoring paradigms and known cognitive and visual traps relevant to these scoring paradigms.

CONCLUSIONS

- Awareness of the gold standard paradox is necessary when using traditional pathologist scores to analytically validate a tIA tool because image analysis is used specifically to overcome known sources of bias in visual assessment of tissue sections.

Effects of high-color-discrimination capability spectra on color-deficient vision

Light sources with three spectral bands in specific spectral positions are known to have high-color-discrimination capability. W. A. Thornton hypothesized that they may also enhance color discrimination for color-deficient observers. This hypothesis was tested here by comparing the Rösch-MacAdam color volume for color-deficient observers rendered by three of these singular spectra, two reported previously and one derived in this paper by maximization of the Rösch-MacAdam color solid. It was found that all illuminants tested enhance discriminability for deuteranomalous observers, but their impact on other congenital deficiencies was variable. The best illuminant was the one derived here, as it was clearly advantageous for the two red-green anomalies and for tritanopes and almost neutral for red-green dichromats. We conclude that three-band spectra with high-color-discrimination capability for normal observers do not necessarily produce comparable enhancements for color-deficient observers, but suitable spectral optimization clearly enhances the vision of the color deficient.

A chromatic diversity index based on complex scenes

We propose a chromatic diversity index based on the Munsell set capable of predicting illuminant induced changes in chromatic diversity of complex scenes. The color differences between complex scenes derived from hyperspectral data under a test and under a reference CIE D65 illuminant were computed and compared with the corresponding differences for the Munsell set. It was found that the average color difference between the complex scenes correlates well with the color differences of the Munsell samples with an average correlation of about 0.94, a result indicating that the Munsell set can be used to predict chromatic changes in complex scenes.