Now the boundary, plotted using trisurf: k = boundary(P) First, the points: P = gallery( 'uniformdata',30,3,5) Legend( 'Original points', 'Shrink factor: 0.5 (default)'. A shrink factor of 1 gives a compact boundary that envelops all the points. A shrink factor of 0 corresponds to the convex hull. The function boundary has an optional shrink factor that you can specify. "But, Steve," some of you are saying, "that's not the only possible boundary around these points, right?" Now compute and plot the boundary around the points. Given a set of 2-D or 3-D points, boundary computes, well, the boundary. The first new function is called boundary, and it is in MATLAB. (I originally planned to post this a few months ago, but I got sidetracked writing about colormaps.) That was one of the shortcomings that the 19 revisions sought to address.Today I'll show you one way to visualize the sRGB color gamut in L*a*b* space with assistance with a couple of new functions introduced last fall in the R2014b release. One characteristic of the commonly used 1931 CIE Chromaticity Diagram that is evident even from this crude portrayal is that the green takes up far too much of the landscape compared to the number of visually different colors in the region. A different observer would likely have chosen different points to represent the color names, but at least these values might provide a starting point for preferred variations. The RGB values obtained are listed in the table at right. The point chosen was just a visual judgment of a representative color in the range. Note that one representative value in about the middle of the hue and saturation ranges was chosen for each section of the diagram. The display here was created by choosing representative RGB values for the color regions from a rendition of the 1976 CIE Chromaticity Diagram provided by Photo Research, Inc. With all those excuses, however, it still might be instructive to provide a rough idea of the regions of the CIE Diagram associated with common color names. Add to that the variations with different kinds of display monitors, and you rightly conclude that an accurate rendition is impossible. Another qualification is that the hue and saturation associated with a given color name can vary over a considerable range. In the first place, you cannot display the range of human color perception on an RGB monitor - the gamut of normal human vision covers the entire CIE diagram while the gamut of an RGB monitor can be displayed as a triangular region within the CIE diagram. The boundaries and the color names are adapted from Brand Fortner, "Number by Color", Part 5, SciTech Journal 6, p32, May/June 1996.Īny attempt to depict the gamut of human color vision on a computer monitor must be accompanied by numerous qualifications and exceptions. These are rough categories, and not to be taken as precise statements of color. Calculation of coordinatesĪpproximate colors can be assigned to areas on the CIE Chromaticity Diagram. The boundary represents maximum saturation for the spectral colors, and the diagram forms the boundary of all perceivable hues. On the CIE chromaticity diagram at left, some annotation is made about the significance of different parts of the diagram. The diagram at lower left is a rough rendering of the 1931 CIE colors on the chromaticity diagram. Revisions were made in 19, but the 1931 version remains the most widely used version. The diagram given here is associated with the 1931 CIE standard. The spectral colors are distributed around the edge of the "color space" as shown, and that outline includes all of the perceived hues and provides a framework for investigating color. The diagram at left represents the the mapping of human color perception in terms of two CIE parameters x and y. Williamson & Cummins, Light and Color in Nature and Art, Ch 3 The colors which can be matched by combining a given set of three primary colors (such as the blue, green, and red of a color television screen) are represented on the chromaticity diagram by a triangle joining the coordinates for the three colors. However, once this is accomplished, it is found that any color can be expressed in terms of the two color coordinates x and y. This system offers more precision in color measurement than do the Munsell and Ostwald systems because the parameters are based on the spectral power distribution ( SPD) of the light emitted from a colored object and are factored by sensitivity curves which have been measured for the human eye.īased on the fact that the human eye has three different types of color sensitive cones, the response of the eye is best described in terms of three " tristimulus values". The CIE system characterizes colors by a luminance parameter Y and two color coordinates x and y which specify the point on the chromaticity diagram.
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