improving bicubic interpolation

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In my on-going research to reduce the filter artifacts noted in  http://bugzilla.gnome.org/show_bug.cgi?id=166130 , I found many references  to a promising improvement on the cubic convolution kernel approach I have  been using.
As noted in the bug report using a convolution kernel entirely removes the  somewhat obvious staircasing produced by the current interpolation at the  expence of a slight softening of the image.
In all the research I have done I have come up constantly to references to  work done by R.G. Keys where he uses 6 point spline fitting instead of the  usual four, but despite extensive efforts I have not been able to find any  reference to the actual piecewise polynomials he derives.
Since the way this technique fits into the code is virtually identical to  the lanczos implementation a six-point approach would envolve exactly the  same calculation effort as lanczos and the larger window and the increased  order of convergence would almost certainly improve the quality and  precision of the filter.
It would seem reasonable to assume this would bring us close to a best of  both worlds situation, a clean interpolaton without the softening.
http://64.233.183.104/search?q=cache:pcUIULp7cboJ:ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19870013008_1987013008.pdf+fourth-order+convergence+catmull-rom&hl=en&ct=clnk&cd=3&client=opera>>Keys’ cubic is a local, six-point inter-polant whose interpolation function is again given bypiecewise cubic polynomials. However, in contrast toPCC, there are no free parameters. The algorithm isfourth order convergent (ref.8) which is the highestorder which can be achieved with cubic polynomials;>>
All references to Keys' work seem to lead to papers published by IEEE and  available on a per article subscription. I assume the charge for one or  two articles would be fairly nominal. Would this be a good use of some of  the gimp projects donations fund?
If the idea is acceptable I'll look into the details.
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