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Equation (6.6) is almost the inverse of Eq. (6.5), and FA (u, v) is the approximation of F (u, v). Inverse cosine transform Eq. (6.2) is then applied to FA (u, v), which gives fA (x, y), the reconstructed image. Since FA (u, v) is an approximation of F (u, v), some differences exist between the original image f (x, y) and the reconstructed image fA (x, y). The compression ratio is dependent on the amount of quantization and the ef ciency of the entropy coding. Figure 6.6 shows the block compression result of a section from a 3-D body CT image volume. The section is compressed using the DICOM JPEG standard (see 9) with a compression ratio of 20:1. Observe the block artifacts shown in the difference image, Figure 6.6C . (See also Figs. 6.19 and 6.20.) 6.4.3 Full-frame Compression
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Potential impacts Assess effects of risks Rating for each element
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In addition to the transparency mask that accompanies every layer (except the background), you can add a mask to a layer to make certain pixels in the layer transparent. Now, you might ask, Won t simply erasing portions of a layer make those portions transparent The answer, of course, is yes. And I hasten to add, that was a keen insight on your part. But when you erase, you delete pixels permanently. By creating a layer mask, you instead make pixels temporarily transparent. You can return several months later and bring those pixels back to life again simply by adjusting the mask. So layer masks add yet another level of flexibility to a program that s already a veritable image-editing contortionist. To create a layer mask, select the layer you want to mask and choose Layer Add Layer Mask Reveal All. Or more simply, click the layer mask icon at the bottom of the Layers palette, as labeled in Figure 12-34. A second thumbnail preview appears to the left of the layer name, also labeled in the figure. A second outline around the preview shows the layer mask is active.
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8.8. APPLICATION OF MATHEMATICAL MODELS IN PRACTICE As was mentioned earlier, practical planning problems usually belong to the class of NP-hard problems, since many complicating practical issues are to be taken into account. The foregoing implies that the computation times for solving instances of these problems usually increase quickly with the sizes of the instances. On the other hand, in practice one may be inclined to take the instances to be solved as large as possible, since decomposition of an instance into smaller subinstances usually leads to suboptimality. In cases where large instances lead to unacceptable running times, one will have to deal with this adequately. One of the following options may be chosen:
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imaged onto the camera. Both the intensity and phase distributions of the wavefront can be measured. An interesting system that can be used for testing the shape or atness of nonoptical parts has been developed based on grazing-incidence interferometry (Synborski, 1978). The system is diagramed in Figure 14.53(a). The component under test is place in close proximity to the hypotenuse of a large glass prism which serves as the reference surface for the interferometer. An air gap is maintained.
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