Hi,
In the manual it says:
The kernel size, default 5x5x5, can be chosen by the user (option: -extent). For maximal SNR gain we suggest to choose N>M for which M is typically the number of DW images in the data (single or multi-shell), where N is the number of kernel elements. However, in case of spatially varying noise, it might be beneficial to select smaller sliding kernels, e.g. N~M, to balance between precision, accuracy, and resolution of the noise map.
With 159 directions, the default kernel size is too small (125). Here there is a little bit of information about this, and how it works.
Best regards,
Manuel