I don't see why you think that a periodic pattern or autocorrelation
function is relevant. Assuming the photo of A contains the four
corners of A, you can use a transformation mapping those four points
to the corners of the output image. I forgot the name of the
transformation, but, the defining qualities are that it is
quadrilateral to quadrilateral and it preserves line straightness. It
is the transformation used in "perspective crop" which you can
google. Of course, you also need the aspect ratio of A which I assume
you measured it before photographing it. Also, you have to
interpolate and you must decide how.
On Jul 17, 1:53=A0am, Palle Uldenborg <palle.uldenb...@[EMAIL PROTECTED]
> wrote:
> Suppose that I have a picture, A, with a fairly consistent replicating
> pattern. So the auto correllation function of A has fairly large
> peaks. Now I take a black/white photograph of A, and I want to use
> this photograph to reconstruct A. The problem here is that the photo
> has extra 3D perspective, so I need to morph the photograph to get rid
> of the 3D effect.
>
> I guess that I have to do something like the following
> =A0* Define a morphing function that morphs the photo.
> =A0* Define a cost function that describes the cost of a morphed photo
> =A0* Look for a global minimum of the cost
>
> I know that the original picture had a replicating pattern, so I guess
> that my cost function can be something like a weighted square of the
> autocorrellation function of the morphed photo. I don't know much
> about morphing functions. Should I use a function that desribes a 3D
> perspective, or should I just choose something fairly general.
> Whatever I do I probably have to worry about local minima of the cost.
>
> In short this is a =A0summer holiday project, and I haven't done a lot
> of =A0image processing before. I would be grateful for some good advice
> and perhaps a few key words so I can do a google search. If you have
> an idea for a good reference book, that ould also be good. I hope to
> be able to do the code in scientific python.
>
> =A0 =A0 =A0 =A0 =A0 =A0 =A0Thanks in advance
>
> =A0 =A0 =A0 =A0 =A0 =A0 =A0 =A0 =A0 =A0 =A0 =A0 =A0 Palle
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