The Colors of Natural Objects and Terrains, and Their Relation to Visual Color Deficiency*

Colors in natural landscapes

“…Not surprisingly, the chromaticities derived from colorimetric computations agree well with the chromaticities reported by Hendley and Hecht (1949), who determined landscape colors by visual matching with Munsell samples, and by Burton and Moorhead (1987), who studied digitized photographs of terrain scenes. Hendley and Hecht call attention to the fact that natural landscape colors have a limited hue gamut.…”

The Demands of Geometry on Color Vision

“…The most obvious candidate for such biases is the distribution of light reflected from natural surfaces. Empirically, the reflectance efficiency functions of natural surfaces give rise to three spectral groups: foliage in the yellow-green region (~557-574 nm); "earths" in the yellow-orange region (~576-589 nm); and water, sky and distant objects in the blue region (~459-486 nm) [20]. These biases accord with the peak sensitivities of the three cone types, which in turn accord with the argument in Figure 6.…”

language impairment and colour categories

“…The natural data set contains 25,000 pixels drawn randomly from photographs of animals, plants, and landscapes; the urban data set contains 25,000 pixels drawn from photographs of buildings, streets, traffic, shops, and other urban scenes. Both data sets have a specific distribution, with an abundance of lowly saturated colours and far fewer highly saturated colours (as already observed by Hendley & Hecht 1949). To allow comparison, a third data set containing 25,000 uniformly random sampled Munsell chips is also used.…”

“…Chromatic data of natural surfaces and the frequency with which these stimuli occur in natural scenes are available (see, e.g., Burton & Moorhead 1987;Hendley & Hecht 1949;Howard & Burnidge 1994), but it is obviously difficult to get data reflecting the ecological importance of colour stimuli for a particular culture and thus the data can never show what aspects of real-world scenes people actually pay attention to. Nevertheless, Yendrikhovskij (2001b) has investigated how colour categories can be extracted from the statistics of natural images.…”