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#!CSeaGreen #!N  #!Rvolrnd Volume Rendering #!N #!EC #!N #!N Another way 
to examine data collected throughout a volume of space is called 
 #!F-adobe-times-medium-i-normal--18*   volume rendering #!EF . Imagine a glass bowl full of 
lemon gelatin. Holding it up to a light, you can see 
through the gelatin because it is somewhat translucent. Now imagine that 
you have added strawberries to the bowl of gelatin before it 
set up. You can see the strawberries embedded in the gelatin. 
What is really happening, visually? Light shines through the mass of 
gelatin "accumulating" color. If you look through the top corner, it 
will appear somewhat less yellow than if you look through the 
thickest part. If the light strikes a strawberry as it passes 
through the gelatin, your eyes will detect an orange object with 
a distinct outline, which of course enables us to find the 
location of the strawberries in the volume of gelatin. The strawberry 
appears orange because its red color is partly occluded by the 
yellow gelatin: nevertheless, our brains convert the strawberry color back to 
red because it is a familiar object. If someone has added 
a fruit unfamiliar to you, you will have a hard time 
identifying the true color of the fruit, since our brains are 
not good at performing subtractive color calculations. #!N #!N Volume rendering 
a data space yields an image something like our bowl of 
gelatin. By default, a volume rendering appears somewhat transparent. As light 
passes through from behind the volume toward your eye, it is 
absorbed more in areas of densely concentrated values. These areas will 
appear to be more "opaque." If you color-map your volume according 
to the data component, you will see indistinct colored areas in 
their relation to each other. For more detail on the "dense 
emitter" model used by Data Explorer, see  #!Lopacom,dxall208 h Opacities Component  #!EL  . #!N #!N 
If we are looking for those areas of rain formation within 
a rain cloud data volume, we do not have a built-in 
conception of the "correct" color for such an area. The colors 
assigned will come from the color map we construct. If we 
map the 12 degree C area to red, as in the 
example above, the red-colored rain-forming areas seen through a yellow cloud 
will, in fact, be perceived as orange areas. We can temporarily 
hide the yellow cloud (by changing its opacity to 0.0 and 
its color to black) and entrain ourselves to see the red 
regions by themselves. #!N #!N This is a fine point of 
perception, but it is important to be aware of. Perception of 
natural objects is greatly modified by psychological memories and judgements about 
their "correctness" in size, color, mass, and relationship to each other. 
Once we move into the abstract world of visualization, we have 
no firm psychological constructs on which to base our perceptions. While 
this may imply that we are working with a "clean slate"--no 
preconceptions, and an unbiased scientific viewpoint--just the opposite happens: we seek 
to impose interpretation on the scene and may ascribe invalid attributes 
to objects as we try to derive "meaning" from the scene. 
On one hand, this is precisely why we imaged the volume 
in the first place! We want to derive patterns or shape 
and then figure out why they exist. On the other hand, 
we can be fooled by our own eyes if we are 
not very careful to comprehend and explain to others exactly the 
assumptions we make as we convert our sample numbers into colored 
images. #!N #!N By the way, you won't find a specific 
module named VolumeRendering. As it happens, any volumetric Field can be 
directly rendered by the Image module or the Render or Display 
modules. So if you simply Import your volumetric data, run it 
through AutoColor, and attach it to Image, you will get a 
colored volume rendering of your data space. #!N #!N #!N  #!F-adobe-times-medium-i-normal--18*   
Next Topic #!EF #!N #!N  #!Lall608,dxall609 h Design for Interactive Use  #!EL  #!N  #!F-adobe-times-medium-i-normal--18*   #!N