[Octave-patch-tracker] [patch #9354] image package: new function wiener2.m

[Hartmut]

Follow-up Comment #11, patch #9354 (project octave):

Thanks for adding the Nd support to the wiener2 function.

I've had a look at your mentioned changeset in your bitbucket repository:

* I think your default value for an Nd neighborhood is generally reasonable.
Also for singleton dimensions. But the most commmon usecase where this will
not be what the user expects are RGB images. For RGB images my expected
default value, if just using wiener2(im), would be nhood=[3 3 1]. But I can
well imagine other 3d data where nhood=[3 3 3] is a more natural default
neighborhood. Maybe we should just write another sentence to the help string
to explain how to properly use this function on RGB images?

* I haven't thorougly check your input checks and parameter juggling. But it
does look reasonable. And my old tests still pass.

* Your new test fails on my linux machine. The absolute errors are on the
order of 1e-4 (except for the 5,5,5 position in one result image, this is off
by 0.0018.) Maybe you should add a looser tolerance to this new test, or is
there a typo somewhere?

I will check the Matlab behavior on logical and empty inputs later. I will
also check the Matlab result for wiener2(ones(1,5)), to make sure how 1d
inputs are treated, I had not checked this before (onyl having 2d images in
mind).

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