🚀 go-pugleaf

sjreeves@eng.auburn.edu (Stan Reeves) writes:

>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?

By normalizing the volume by the surface area, the value of the measure 
can be compared for different size of images.

>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.

The Mean-Square error is kinda L2 metric.
Apparently, if MSE is used as a measure, where the slope is high,
the difference value is emphasized more than in flat regions.
I am saying that MSE measure is ** not invariant ** w.r.t. a coordinate system.
The original poster was looking for methods to compare various algorithms on
image restoration, wasn`t it ?

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


-- yi@ecn.purdue.edu