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Pure spectral

Figure 12.23 Example of multivariate curve resolution (MCR). (A) A series of 210 FTIR. spectra obtained during the course of a chemical reaction (B) the pure spectral profiles obtained using MCR. and (C) the corresponding pure concentration profiles obtained using MCR. Figure 12.23 Example of multivariate curve resolution (MCR). (A) A series of 210 FTIR. spectra obtained during the course of a chemical reaction (B) the pure spectral profiles obtained using MCR. and (C) the corresponding pure concentration profiles obtained using MCR.
Figure 3. The three pure spectral colors, the prime-colors, uniquely related to normal human vision. Combined, as shown here, they form a white-light mixture the color of sunlight. Figure 3. The three pure spectral colors, the prime-colors, uniquely related to normal human vision. Combined, as shown here, they form a white-light mixture the color of sunlight.
Figure 8.35 Estimated pure spectral profiles extracted from the FTIR spectra obtained during the chemical reaction, using SMCR. Figure 8.35 Estimated pure spectral profiles extracted from the FTIR spectra obtained during the chemical reaction, using SMCR.
The pure spectral profiles corresponding to each of the components (Figure 8.35) can be used to provide further information regarding the nature of the pure components that are represented in the concentration profiles. This is especially the case if one uses prior knowledge regarding the spectroscopic technique (more specifically, band assignments for specific functional groups in the process material). [Pg.307]

Figure 1.8 Colour triangle . Any perceived colour is represented by a point in the area enclosed by the curved line. The wavelengths of pure spectral colours are shown in nm... Figure 1.8 Colour triangle . Any perceived colour is represented by a point in the area enclosed by the curved line. The wavelengths of pure spectral colours are shown in nm...
Newton also discovered that the blending of pure spectral colors produced new composite colors. He found that blending only spectral red, green and blue light in various proportions produced essentially all other colors. Thus, these three colors are commonly called the primary colors. [Pg.198]

Third Law Every color except pure spectral colors can be made from any of a large number of combinations of color sources, and those composite colors produced will appear indistinguishable to an observer. [Pg.204]

The good news from this chapter is that all of the techniques we have used in this book so far are applicable in two and three dimensions. The bad news is that things are generally more complex in higher dimensions. Meshes are the most general way to model the spatial aspects of vibrations, and modes are the most general way to handle the pure spectral behavior. Banded waveguides are applicable in some systems, especially where clear, closed wavepaths can be identified. The next chapter will depart entirely from these types of models, and look instead at the statistical behavior of random type sounds. [Pg.146]

FIGURE 13.6 Chromaticity diagram containing the CIE chromaticity triangle associated with pure spectral colors. [Pg.346]

Fio. la. Maxwell triangles (triangular co-ordinates). The color triangle obtained by use of primaries red, blue, and green (B, 0, and B) chosen for convenience or availability. They do not have to form an equilateral triangle, nor is white necessarily at the precise center. Even if pure spectral colors had been selected, the plot of the spectrum locus shows that no three real primaries can be selected which will match all possible colors. [Pg.304]

The X and y chromaticity coordinates are typically plotted in a two-dimensional grid known as the CIE (x,y)-chromaticity diagram (Fig. 14.8). The curve is made of the pure spectral colours from the blue to the red, covering the entire visible... [Pg.501]

Chroma The deviation of the color from gray. Pure spectral colors such as red and violet have high saturation. Saturation refers strength of the dominant wavelength or hue. Pink and red have the same hue but differing saturation. [Pg.470]

The principal components are not pure spectral components but contain portions of all the pure chemical components, the interactions between the chemical components, and the instrument artifacts. The principal components are determined by an iterative process whereby the most significant principal component is determined first and subsequent principal components have successively smaller contributions. [Pg.214]

Tel Aviv, Israel. Data acquired by the Digital Airborne Imaging Spectrometer (DAIS) have been used by Roessner et al. (2001) to obtain a map of urban materials in the city of Dresden, Germany. In this study, a maximum likelihood classifier has been used to derive a first map of pure spectral features and then used these feamres to unmix the other spectra. [Pg.1161]


See other pages where Pure spectral is mentioned: [Pg.406]    [Pg.411]    [Pg.414]    [Pg.403]    [Pg.200]    [Pg.305]    [Pg.167]    [Pg.147]    [Pg.147]    [Pg.138]    [Pg.12]    [Pg.307]    [Pg.315]    [Pg.304]    [Pg.502]    [Pg.293]    [Pg.305]    [Pg.469]    [Pg.15]   
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