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The process of device-independent color imaging described by Figure 19.1 illustrates the necessity of color appearance models. There are two main needs for these models image editing and viewing-condition transformations. Image manipulations such as color preference reproduction and gamut mapping are best performed in the perceptually signi cant dimensions (e.g., lightness, chroma, and hue) of a color appearance model. Clearly the transformation of colorimetric coordinates from one set of viewing conditions (white point, luminance, surround, medium, etc.) to a second set of viewing conditions requires a color appearance model. The only way to avoid the use of a color appearance model in deviceindependent color imaging is to specify a rather strong set of constraints. The original and the reproduction must be viewed in the same medium, under identical viewing conditions, with identical gamuts, and with the objective of colorimetric color reproduction. In such a constrained world, colorimetric and color appearance reproduction are identical. Clearly, the above constraints are far too severe for all but the most specialized applications. Thus the use of color appearance models in device-independent color imaging is unavoidable if high-quality, reliable results are to be obtained in open systems.

5 6 7 8

Figure 13-19: To add color to a table s background, choose the borderColor attribute from the table tag s pop-up menu in Outline mode.

(b) The flux of 2.225 MeV prompt gamma rays released by (n,c) reactions in hydrogen is determined by the number of (n,c) reactions, or

// Displays 2 times 3 is 6. printf( %d times %d is %d. , 2, 3, 2*3 );

31 The substitutes that were developed, the hydrochloro uorocarbons (HCFCs) and hydro uorocarbons (HFCs) are transitional substitutes. Both are greenhouse gases, and HCFCs are also ozonedepleting substances although signi cantly less so than the CFCs they replaced.

The similarity between this algorithm and the many PSI algorithms, especially the synchronous detection algorithm in Eq. (14.171), should be apparent. Similar systems have been built that image the interferogram onto a segmented detector, and the individual outputs are sinusoidally weighted to determine the phase (DeCou, 1974; Mertz 1983a,b, 1989). The Fourier analysis methods provides a virtually identical analysis, but the computations are done in the spatial frequency domain instead of the spatial domain (Takeda et al., 1982; Macy, 1983; Nugent, 1895; Bone et al., 1986; Kreis, 1986; Roddier and Roddier, 1987). An interferogram pattern with tilt as described by Eq. (14.178) can be rewritten as I x; y I 0 x; y c x; y ei2pf0 x c x; y e i2pf0 x where c x; y I 00 x; y =2 eif x;y 14:185 14:184

You can use several shortcuts when working in dialog boxes that open or save files, as follows: Double-click the drawing file to open it immediately without clicking Open. Click the Views drop-down list. Choose List to see a simple list. Choose Details to see the file size and the last date and time the file was saved. Right-click inside the dialog box to open a shortcut menu with more options. Click the name of a drawing to highlight it and then click it once more to rename it (but don t double-click it that opens the drawing).

The Big Bang model does not give a unique description of our present Universe, but rather leaves quantities such as the present expansion rate, or the present composition of the Universe, to be fixed by observation. It is a standard practice to specify cosmological models via a few parameters, which one then tries to determine observationally to decide which version of the model best describes our Universe. In this chapter and the next I'll discuss the most commonlyconsidered parameters, including ones we have already seen and new ones.

Obesity predisposes to type 2 (non-insulin dependent) diabetes, and is largely responsible for the current pandemic of the disease, which is predicted to double the number of diabetic people worldwide in just 30 years, from 150 million in 1995 to over 300 million in 2025 (see s 2 and 10). The association between obesity and type 2 diabetes was highlighted in classical studies of isolated ethnic groups which, after centuries of active and frugal existence, had suddenly become sedentary and overfed. Notable examples were the Pima Indians living near the Gila river in Arizona and the inhabitants of the Paci c island of Nauru (Figure 1.11).