🚀 go-pugleaf

In article <yi.714841254@fife.ecn.purdue.edu> yi@fife.ecn.purdue.edu (Juneho Yi) writes:
>m_yearwo@csd.brispoly.ac.uk (Mike Yearworth) writes:
>>	I'm looking for some references on extracting objective
>>measurements of image quality, for example the signal to noise ratio
>>of an image or its entropy, with a view to judging how good a particular
>>image restoration technique is. I'd be interested in obtaining bibliographies
>>and/or references to good textbooks. Thankyou.
>
>We use the volume between two surfaces(original image and restored
>one)normalized by the surface area
>as an invariant(w.r.t. arbitrary coordinate) measure to compare
>results from different reconstruction algorithms.
>We came up with a very efficient way of computing
>the volume between
>two surfaces and the surface area. Time
>complexity is theta(n)
>where n is the number of pixels. 

I'm assuming that the original poster is interested in objective measures
that have some correlation to the assessment a human observer would make.
Does this measure have any relationship to subjective evaluation?  What is
the point of normalizing with respect to surface area?

The simplest objective measure is mean-square error, but it doesn't always
correlate closely with a subjective evaluation of image quality.  Granted, 
the above technique is *an* objective measure, but the question is whether 
it is a good one for the purposes of the original poster.


--
Stan Reeves
Auburn University, Department of Electrical Engineering, Auburn, AL  36849
INTERNET: sjreeves@eng.auburn.edu