Hi all,
I would like to do the pca (principal component analysis) of my Sentinel-2 multiband image composed of nine 20m-L2A rasters. I tried with the otbcli_DimensionalityReduction module (the method parameter was set to “pca”), but the statistics of the output image is not as I expected. Namely, all the bands of the output image has the standard deviation equal to 1. Generally, I expected that the output pca bands have standard deviations different from 1. This would then allow me to select the most significant bands according to the variance loss criteria. Is this a bug of the DimensionalityReduction –pca algorithm, or there is maybe another way in orfeo toolbox to get the pca bands without std normalized to 1? Thank you in advance for your time and the help! Cheers, Kimi PS. I am using orfeo 6.4.0 from the command line, and there is my code: >>otbcli_DimensionalityReduction -in test2.tif -out pca_norOFF.tif -method pca -normalize 0 >>otbcli_ComputeImagesStatistics -il pca_norOFF.tif and this is the statistics for 9 bands from the pca output image: Mean: 2.14067, -1.29191, 0.554654, 0.996805, -0.267422, 0.423317, 0.285117, 0.281447, -0.183358 Standard Deviation: [1, 1, 1, 1, 1, 1, 1, 1, 1] My input multiband image can be downloaded from here: https://files.fm/u/2vh7aqvu -- -- Check the OTB FAQ at http://www.orfeo-toolbox.org/FAQ.html You received this message because you are subscribed to the Google Groups "otb-users" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/otb-users?hl=en --- You received this message because you are subscribed to the Google Groups "otb-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
