Re: Projective image transformations

On Saturday 14 September 2002 11:04 am, Keith Packard wrote:
[...]
|
|  > My understanding is that resampling really means "reconstruct (a
|  > continuous representation of the signal), filter, then sample."
|
|  In the DSP world, resampling is done by upsampling to the LCM, filtering,
|  downsampling to the target sample rate and then filtering again.  I think
|  this is essentially the same thing.  Of course, implementations generally
|  have just a single FIR that walks over the input and generates the output,
|  but the filter coefficients contain the composite of both filters and the
|  resampling stages.
|
|  Nearest neighbor is the simplest form of this; it's just a box filter,
|  which isn't particularily good at reconstructing the signal, nor does it
|  effectively eliminate aliasing as it doesn't clip values above the Nyquist
|  limit.
|
|  I guess bilinear interpolation can be considered a filter as well, kind of
|  a two element FIR.
|

Of course bilinear interpolation should be considered a filter!

|  > Hard to tell where this technology is going from a point of view outside
|  > the IHVs, but I'd bet we'll see more options.
|
|  I think that just means we need to make sure the set of filters we allow
|  is extensible.  Owen had a suggestion that we provide aliases for virtual
|  filter names like "fastest", "smooth-but-not-too-slow", "best-results" so
|  that applications could use these names instead of attempting to pick one

Sounds good and reasonable.
By the way, please do not limit filter matrix size to 3x3 or 5x5.
Modern computers have a lot of power. So I think 9x9 or 11x11 matrixes should 
be ok (in terms of resource spent) for modern (Pentium III/600+) computer.

|  of the physical filter names.  That would permit redirection of
|  applications using the generic names to specific filters which provided
|  the expected performance tradeoff.
|
|  Keith Packard        XFree86 Core Team        HP Cambridge Research Lab
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