actually, having read that, I have to change it a bit. If you have a large
image and good reason to expect that overall (in all directions) you have
the same average spacing and that drift on the AFM is your greatest source
of error, you only need to average the longest and shortest and call the
range the error. If you have no drift, then the gaussian method may be
best. Your sample image is so small that the lamellae mostly run in one
direction - probably in this case I would pick the direction with the
strongest intensity (i.e. most information) and do the gaussian method on
that.
On 1 September 2011 11:54, Joe Smerdon <[email protected]> wrote:
> Although there is probably a rigorous way of doing this, I wouldn't really
> try. Since inside the region of intensity you will get additional peaks
> (from multiples of the primary separation) you are only really interested in
> the point at which the intensity starts i.e. the outer edge. I personally
> would fit that with one half of a Gaussian, call the sigma the error and
> average over all directions (to a first approximation, just the directions
> which identify the bounds of the distribution i.e. the longest and the
> shortest). I don't think it matters that this is not particularly rigorous
> as it's a pretty fuzzy number in the first place. I don't know about
> tutorials - I have thought about writing some, but the people who would read
> them probably number in the 1s.
>
> Joe
>
>
> 2011/9/1 Lewis Williams <[email protected]>
>
>> Joe,
>> Thank-you very much for the help.
>>
>> I think I've gotten my head around extracting the d-spacing. But I'm not
>> sure about the error.
>> Which points of a line profile over the fft would correspond to the error?
>>
>> Is there a more in depth tutorial on looking at spacing in this manner?
>>
>> Lewis
>>
>>
>> On 31/08/2011 22:35, Joe Smerdon wrote:
>>
>> for a large scale image with lots of information, a 2d fft should show a
>> (diffuse) ring of intensity showing the average (inverse) spacing. a line
>> profile over the diffuse ring might give you something to fit to find the
>> error on the measurement.
>>
>> if i open your phase image, then do a 2d fft, then use the colour tool to
>> optimise the colour range, i find a domain of intensity clustered around the
>> middle - this (obv) is related only to the low frequency information and the
>> stuff around the outside is related to the high frequency (to pick the
>> frequency range you are interested in you can use fft filtering). well, the
>> lowest frequency stuff i can find in the image is the domain spacing, so i
>> just pick the frequency that fits the domain of intensity, invert it and i
>> get an average spacing for your image of about 14 nm. a line profile of the
>> fft gives me an error of about 1 order of magnitude, so about 1.4 nm.
>>
>> hth
>>
>> joe
>>
>> On 31 August 2011 14:39, Lewis Williams
>> <[email protected]>wrote:
>>
>>> I was wondering if somebody could help me with the correct/best way to
>>> process my images.
>>>
>>> I'm trying to extract the average domain spacing from tapping mode AFM
>>> images.
>>> I have a lamellae structure, and I'd like to know the average
>>> interdomain spacing.
>>>
>>> I can extract a profile and then measure peak to peak and then average
>>> the values, but this is only averaged in 1 dimension over a chosen
>>> profile.
>>>
>>> Please advise.
>>>
>>> Sincerely,
>>> Lewis
>>>
>>>
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>>
>>
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