On 04/12/13 15:22, Nikos Alexandris wrote:
Nikos Alexandris wrote:
The i.pca module in G7 offers a "forward/filtering/backward" PCA. I have
an issue first with filtering and second with rescaling.
1) I can't see any differences in the derived Principal Components
okay, to clarify: I mean the resulting images which, initially are Principal
Components (synthetic images) and, after applying filtering & backward PCA,
the resulting images approach the original data -- still they are modified.
between percent=70 and percent=99 for 4 bands which the PCs (both centered
and scaled) are:
PC1 2.78 ( 0.4947, 0.5922, 0.5743, 0.2735) [69.53%]
PC2 1.08 ( 0.5196, 0.0517,-0.0974,-0.8473) [26.99%]
PC3 0.11 ( 0.4210, 0.2486,-0.7926, 0.3644) [ 2.86%]
PC4 0.03 (-0.5551, 0.7647,-0.1805,-0.2729) [ 0.63%]
What is filtering doing actually? Shouldn't percent=70 just filter out
the rest, somehow?
Moritz Lennert wrote:
AFAIU, filtering happens after pca: pca is run on all bands, then
according to the filter percentage you chose inverse pca is run using
the principal components necessary to reach the filter percentage of
variance. In your example, 70% would use PC1 and 2 (unless variances is
rounded up) and 99% would use PC1,2,3. Any difference you see is in the
resulting images, not in the PCA.
Sure -- I didn't (mean to) state otherwise. But, there are no differences in
the resulting images (after PCA > Filtering > Backward PCA). Makes sense?
Apologies for not being very clear.
Here I see a difference:
> r.info -r lsat7_2002_10
min=42
max=255
> r.info -r filt.1
min=49.4097659695008
max=200.074494678242
> r.info -r lsat7_2002_20
min=28
max=255
r.info -r filt.2
min=29.93376973921
max=204.43559249011
etc.
Moritz
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