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Re: RMS error [message #39376 is a reply to message #39375] Wed, 12 May 2004 07:56 Go to previous messageGo to previous message
Paul Van Delst[1] is currently offline  Paul Van Delst[1]
Messages: 1157
Registered: April 2002
Senior Member
Craig Markwardt wrote:
> David Fanning <david@dfanning.com> writes:
>
>
>> Julio writes:
>>
>>
>>> I'd like to calculate Root Mean Square error using a base image and a
>>> secondary image. How can I do that? Clues are welcome!
>>
>> rms_error = Sqrt( Total((img_1 - img2)^2)/N_Elements(img_1) )
>
>
> Hey David, I'll pile on too. The problem I see with the above
> expression is that there could be an offset between the two images,
> which you are including in your TOTAL expression, and hence biasing
> the rms value.

Errmm... isn't that intended? RMS errors include the bias. Std deviations don't. At any
rate, that's how I use 'em. This is what I've got on my wall:

RMS = SQRT( TOTAL( Xtruth - Xpredicted )^2 / N )

and

StdDev = SQRT( TOTAL( Xpredicted - MEAN(Xpredicted) )^2 / N )

I think it really requires the OP to state more precisely what it is he's looking for.
Blind use of statistical formula is usually a no-no.

> rms_error = stddev(img_1 - img2)

That works - same as the RMS defn above where Xtruth = img1-MEAN(img1) and Xpredicted =
img2-MEAN(img2). But is that what the OP needs/wants?

paulv
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