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Re: New Image Processing Routines [message #48448 is a reply to message #47726] Mon, 24 April 2006 21:47 Go to previous messageGo to previous message
Marshall Perrin is currently offline  Marshall Perrin
Messages: 44
Registered: December 2005
Member
David Fanning <davidf@dfanning.com> wrote:
> As a working hypothesis I think my "nonlinearity" parameter
> doesn't directly correlate with Lupton's "beta" parameter,
> but I think this is because I scale the image data into
> the range of 0 to 1 before I apply the scaling. This is
> necessary, in my case, because I can't rely on image data
> values falling into a particular range. I need to start
> with something I can depend on.

I think that you're correct here, but the "right" correlation between
nonlinearity and beta isn't too hard. To convert Lupton's beta into
nonlinearity, we just have to account for what Scale_Vector is doing,
right?

scaled_beta = (beta - MinValue) / (MaxValue - MinValue)
nonlinearity = 1./scaled_beta

This is actually a useful way to parametrize things, because then
you can let beta equal whatever you think the noise level in the
image is, and the above code will compute the nonlinearity factor
which lets you simultaneously see the noise *and* the image maximum.
So I don't know if beta is actually -entirely- obsolete just yet.
Alpha, now, that's another story. :-)

- Marshall
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