- The assumption of the method used in dwidenoise is that in a local patch the noiseless signal is sparse and can be represented using a low dimensional projection of the measured signal. Noise on the other hand is not sparse. I think, for this decomposition, the actual size of the voxels should matter much less than the extent in voxels.
- That depends on whether the images share the same noise characteristics. Did you see this related question? Use of Prescan Normalize (Siemens) and dwidenoise
If you go for concatenation and splitting, you can use mrconvert's -set_property and -get_property to manually set the transformations back to their original values.