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gtzpower

Library or advice for synchronizing heightmaps of different tessellations?

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Hi everyone. I am tasked with synchronizing 2 tesselations of heightmap data where the sample spacing of the second height map is dynamic (one set of data may have a 20 cm sample spacing where as another set of data may have a 1 meter sample spacing, and I need to be able to apply both to my height map as best as I can). I need something that will take height data (rows and columns of floats), a source sample spacing and a destination sample spacing, and have it return the best fit for representing the data with the new sample spacing. If that doesn't make sense, refer to the graphic below. I want to pass in the red data and get back the blue data as shown in the AFTER part:

[img]http://www.spudgames.com/stuff/tessellation.png[/img]

Alternatively, if this type of functionality is not readily available, are there any tips on how to mathematically do it?
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Let me rephrase your question to see if I understand it: If you have data at points of a particular grid, how do you infer the value at a different set of points?

This can be reduced to: If you have data at points of a particular grid, how do you infer the value at an arbitrary point?

The answer is "[url="http://en.wikipedia.org/wiki/Interpolation"]interpolation[/url]". Your plot suggests that you want linear interpolation of the data, which is fairly straight forward (in 2D there is [url="http://en.wikipedia.org/wiki/Bilinear_interpolation"]bilinear interpolation[/url]), and it's even available in hardware on graphics cards. In general, there are many interpolation algorithms that can be used for geographic data. Some are [url="http://en.wikipedia.org/wiki/Kriging"]quite sophisticated[/url]. I would say, if you are happy with the results of bilinear interpolation, go with it. But for some purposes it won't be enough.
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Thanks! Bilinear interpolation is the phrase I was looking for which will help me find something. A glance at wikipedia reveals an equation that I had independantly came up with, but I wasn't sure if ithe theory would hold up. So that answer is spot on! :) Thanks again!
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