Currently, I am working with ALOS-2 PALSAR-2 data. I just want to know-
- Which filter should be best for my data?
- How to choose speckle filter parameters (e.g.- if I choose Lee Sigma filter, what should the number of looks, window size, sigma value, Target window size)?
- Actually I want to get the radiometric terrain corrected data. In which phase I should use the speckle filtering?
- Should I use speckle filtering on the ‘Beta0’ value?
about the filter: There is no right or wrong. They all have their right to exist, they were developed and published by different people at different times. In the end, they do similar things, reducing speckle to a certian degree. So it really depends on your application and what you want to extract from the later product. If you need point-like or linear features, you select smaller window sizes to preserve edges, but if you are working on larger areas (e.g. agricultural fields), you can apply a more aggressive filter to get homogenous areas. The best advice I can give is to try and compare.
Filtering before terrain correction should be the better choice, because most filters were designed for data in slant geometry.
You only need Beta0 if you want to apply radiometric terrain flattening afterwards. If not, you should apply the filter on Sigma0.
This might also clarify: Radiometric & Geometric Correction Workflow
Hi Andreas @ABraun,
I am using this topic to ask again for your help with something related to it.
I am working on a project on coastal monitoring using S1 and I am using SNAP to pre-process the data.
As you suggested in other topics I have applied the speckle filter before the terrain correction but I have two questions about the preserving of the edge detection of the coast:
Which filter is better on this matter? I know your suggestion to try more than one and then compare the results but maybe you could help me to reduce the list of possible filters to test.
In TC which DEM resampling and image resampling method do you suggest to preserve as much as possible the coastline? I am using for both “BILINEAR INTERPOLATION” but I have seen that you in another topic suggested “NEAREST NEIGHBOUR”.
Thank you always for your support and advice.
I really can’t recommend any filter over others, this totally depends on the spatial resolution, the data and the nature of the image.
I don’t think resampling affects the results here, but you should disable “mask areas without elevation” to preserve the sea areas.
Yes @ABraun, I see what you mean.
Just to clarify, I am using GRD images and the processor creates a Waterline differentiating between land and sea and the pixel spacing is 10m x 10 m.
My question was related to which filter preserves better than other the edge detection between land and sea and moreover if the resampling method in TC could have some effects on it.
“Mask areas without elevation” is already disabled.
to a certain extent, all radar filters are edge preserving. But it depends on the contrast between land and sea which fits your case the best. You can create a small subset and test/compare the few available.