Concerning the calculation of the color gamut in a digital camera

Abstract

(Y between 40 and 70, or L* between 69.5 and 87.0). This behavior is due to the short dynamic range of the digital camera response

Computation and visualization of the MacAdam limits for any lightness, hue angle, and light source

“…This proposal could be used as an alternative method to the (relative) color-rendering algorithm 20 proposed by CIE. The proposed methods in these calculations could also be used to evaluate and compare color gamuts of color-imaging devices [34][35][36] and even of other natural vision systems (dichromacy, trichromacy, etc.). However, it seems adequate to work more much in the future with a colorimetric parameter for classifying illuminants and real lamps, taking into account both the volume (number of distinguishable colors) and the shape of the associated color solid.…”

“…Therefore, we think that much more work is needed, for instance, testing a spheres-packing method in the most uniform color space available, in order to make a careful study of this subject concerning the colorimetry of light sources and color perception. However, these methods and their preliminary results could be useful to develop new applications in color imaging, as, for instance, comparing the color gamuts of color devices, [34][35][36] and in lighting design (museums, sports, TV, cinema, etc.). This could even be applied in order to evaluate the distinguishable colors of animal vision, such as dichromatic, trichromatic, or higherdimensionality vision, provided that the internal model of chromatic discrimination and encoding was known for each species.…”

Spectral reflectance estimation of organic tissue for improved color correction of video-assisted surgery

“…With this in mind, one can easily imagine that a more or less perfect color reproduction and, therefore, negligibly small colorimetric errors are crucial for the success of a surgery, where different kinds of tissues must be distinguished by the surgeon not only through their texture but also through their color. However, perfect color reproduction is usually not the case because, in general, the RGB-sensor of a digital camera system does not fulfill the required Luther-Ives condition, [8][9][10] i.e., the spectral response curves of the RGBsensor cannot be described as a linear combination of the eye cone response functions. As a consequence, more or less severe colorimetric errors occur when comparing the direct perception of the surgical field to its reproduction.…”

Effectiveness of Digital Camera Sensors in Distinguishing Colored Surfaces in Outdoor Scenes

“…The effectiveness of a sensor was quantified by the number of surfaces that could be distinguished. This experimental measure is a generalization of the notion of color sensitivity or input gamut [3][4][5][6][7], normally defined for uniformly sampled colors in some theoretical color space (and sometimes expressed as a percentage of the maximum number, e.g., 256…”

“…For independent channels, this number is much less than (SNR) 3 , where SNR is the signal-to-noise ratio (mean divided by standard deviation [12,14] ).…”