| Image comparison and tricky shortest vector problem [message #39861] |
Fri, 18 June 2004 06:40 |
matt_westmore
Messages: 4
Registered: June 2004
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Junior Member |
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Hi group,
I'd really appreciate some help with the following problem.
Essentially I have two images I want to compare. My comparison
criteria is based on the difference in intensity values and also on
the differnece in distance between two points that have similar
intensity values.
For each pixel in the first image I need to find the (inter-pixel)
point in the seccond image that minimises the length of the following
vector.
G = (x2-x0)i + (y2-y0)j + (d2-d0)k
where x0,y0,d0 is the x,y and intensity of the PIXEL in the first
image
where x2,y2,d2 is the x,y and intensity of the POINT in the seccond
image
It's not a straight forward min() problem becasue the minimum
condition could (and normally is) met between pixels in the second
image; i.e. effectively I need to interpolate.
I'd be greatful for any advice.
Cheers
Matt
Some Background(For those in the know)
======================================
I'm comparing radiotherpy dose distributions and so I've implemented
the Gamma index. This is effectivly the length of a vector that joins
two pixels in two dose distributions. Gamma is of the form
(dx,dy,ddose); i.e. consists of the diference in distance between the
two points and the difference in dose. The task is to search a
secondary dose distribution to find the minimum value of gamma fro
each pixel in the primary dose distribution.
The problem is that my implementation is approximate and very very
slow as I interpolate the secondary dataset to a fine scale and filter
for the minimum gamma. This done for each point in th first image with
a for loop.
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