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I'm doing plate reduction on astro photos. There's non-linearity in the
lens. Basically, one is trying to estimate several lens parameters by
look at a field of known stars versus ones measured on a photo plate.
The author states it can be solved by taking first derivatives to
linearize matters, and iteratively apply least squares until the change
in parameters falls below some limits. Gauss-Newton seems a bit
different in that it tries to minimize the sum of squares. In a follow up paper, he refers to the process as a gradient method. Up until then, my best guess was G-N. I suspect that you are hinting at the Gradient plus LSQ (least squares). However, out of curiosity, isn't their a library of optimization methods like Marquardt or Davidon? On 5/28/2010 12:09 PM, Charles R Harris wrote: What problem are you trying to solve. The leastsq algorithm in scipy is effectively Gauss-Newton when that is appropriate to the problem. --
Wayne Watson (Watson Adventures, Prop., Nevada City, CA)
(121.015 Deg. W, 39.262 Deg. N) GMT-8 hr std. time)
Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 feet
There are no statues or memorials dedicated to
Thomas Paine for his substantial part in the
American Revolution.
-- An observation in The Science of Liberty
by Timoth Ferris
Web Page: <www.speckledwithstars.net/>
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