Two questions. (1) I've been using the TotalVariationDenoisingImageFilter on 3D reconstruction images with impressive results. Now I'm trying to apply TV denoising to my 2D projection images as a preprocessing step, however I'm not seeing the same denoising results as with 3D images. Was this implementation of TV designed to handled 2D images? I've experimented with a range of Lambda values, including the Lambda value that produced good results when applied to my 3D reconstruction image (about 5.0).
(2) I've browsed through the code a bit, but haven't found how the iterative TV filter is setting the step size. I'm assuming that since step size is not an imput parameter, this must be using a adaptive step size scheme. Is this true? Can someone describe how this is being done or point me to the lines of code that are doing this? On a side note, are there plans to try to get this filter integrated into mainline ITK? Thanks for the help, Taylor ------------------------------------------------------------------------------ AppSumo Presents a FREE Video for the SourceForge Community by Eric Ries, the creator of the Lean Startup Methodology on "Lean Startup Secrets Revealed." This video shows you how to validate your ideas, optimize your ideas and identify your business strategy. http://p.sf.net/sfu/appsumosfdev2dev _______________________________________________ mitk-users mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/mitk-users
