Hi everyone,
I have a query and a request; query about how to make effective per-processing steps in AVIRIS (Hyper- spectral) data processing? I have done some steps like empirical calibration, MNF and some more. But i could not remove noises from radiance data. So in this situation, my kind request to you all if anybody has experience, knowledge or expertise, please en-light me with yours wisdom.
Add on: If you can please attach some link or literature of good publications related to pre-processing of AVIRIS data.
Thank you
Hi, (sorry for the English)
So, the pre-processing depends on the type of processing will be done. You can perform a low pass filtering to reduce the noise, using higher kernel's for more noise reduction, but for classification it can not be good. Maybe you can performe a high pass filtering using fourier transform direclty on the tranformed space information, there you have a more control over signal that you need to remove.
Hi,
if you consider not geo-corrected radiance data we can give this approach http://dx.doi.org/10.3390/rs61111082 (most pushbroom sensors are affected by temporal variations of the dark current and related miscalibration) or this approach http://dx.doi.org/10.3390/s110606370 a try else there are some smoothing techniques as Atilio said.
Cheers, Chris
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