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As someone who has worked on "both" interpolations and image compression in a geoscientific context, the issue is specifically what is the model for the signal.
by fghorow 6y ago
As someone who has worked on "both" interpolations and image compression in a geoscientific context, the issue is specifically what is the model for the signal. If the model is accurate enough, then yes, removing independent noise is of great value.
In my worldview, the big problem is what is the physics behind the signal, and where precisely does it change from one characteristic class to another.
Those are the hard problems.
- ISL 6y agoIndeed, to apply any form of "denoising" is to presuppose what the "true" underlying sample looks like. All of these strategies that people like to apply, whether they know it or not, directly impose a model onto the initial dataset. Once measurements are digitized, the uncertainty within the dataset is baked in and cannot be removed. Without external information, the best estimation of the distribution from which the data are drawn may be found within the data themselves.