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yes you are on the right track. The classic way to do that is the
maximum noise fraction transformation (MNF), which consists
basically of two chained PCAs: <br>
<br>
Green et al (1988) A transformation for ordering multispectral data
in terms of image quality with implications for noise removal. IEEE
Transactions on Geoscience and Remote Sensing<br>
<br>
Unfortunately I'm not aware of a free, readily usable
implementation. Orfeo toolbox is close, but does not yet provide a
packaged command to do it.<br>
From proprietary software, I remember that ENVI had a MNF function.<br>
<br>
<br>
<div class="moz-cite-prefix">On 02.03.2017 19:29, Natalia Quinteros
wrote:<br>
</div>
<blockquote
cite="mid:CAOZBhq0TxQnO34e==Qhs4C301XVBgeTVAB9j_NsQnsfSU2dznQ@mail.gmail.com"
type="cite">
<div dir="ltr">Hi list,
<div><br>
</div>
<div>I'm working with hyperspectral images and I need to get rid
of the bands with poor signal-to-noise ratio. I was wondering
if somebody have done that and if you could give me some
advise. I'm looking at a paper right now that does that for
multispectral images using PCAs. </div>
<div><br>
</div>
<div>Thanks </div>
<div><br>
</div>
<div>Natalia</div>
</div>
<br>
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<pre class="moz-signature" cols="72">--
Benjamin Leutner M.Sc.
PhD candidate
Department of Remote Sensing
University of Wuerzburg
Campus Hubland Nord 86
97074 Wuerzburg, Germany
Tel: +49-(0)931-31 89594
Email: <a class="moz-txt-link-abbreviated" href="mailto:benjamin.leutner@uni-wuerzburg.de">benjamin.leutner@uni-wuerzburg.de</a>
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