NDSAR, a multi-dimensional nonlocal speckle filter

The NDSAR filter comes in two versions:

• The NDSAR-BLF is a bilateral filter adapted to covariance matrices obtained from SLC multi-dimensional images.
• The NDSAR-NLM is a generalization of the previous method which computes similarities on square patches instead of individual pixels. It is more robust to speckle than the bilateral but requires more computational power, depending on the user selected patch size.

I have released the open source Python/C++ implementations of the filters based which can be applied to any type of SAR data (Polarimetric, Tomographic, Inteferometric, Multi-temporal, PolInSAR).

Equivalent filters for single channel i.e. intensity images are also provided (special case of 1x1 covariance matrix).

Here is an example of an F-SAR image (DLR) filtered with NDSAR (left: original, right: filtered):

The figure below shows the impact of NDSAR on 3-D point cloud extraction from multi-baseline interferometric data (also called SAR tomography):

Source code on github

More information can be found in the following publications:

O. D’Hondt, C. López-Martínez , S. Guillaso and O. Hellwich. Nonlocal Filtering Applied to 3-D Reconstruction of Tomographic SAR Data. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56, 272-285

O. D’Hondt, S. Guillaso and O. Hellwich. Iterative Bilateral Filtering of Polarimetric SAR Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013, 6, 1628-1639