[Insight-developers] Proposed class: Fast Bilateral Filter

[Luis Ibanez]

Hi Jordan,

This is great !

I'm not aware of an alternative implementation for the
BilateralImageFitler (for ITK).

It will be great if you implement this fast variant and
contribute the code to the Insight Journal.


Please let us know if you have any questions
about how to proceed,


    Thanks


       Luis


-----------------------
Jordan Woehr wrote:
> Dear Insight Developers,
> 
> I have been assisting in research on a project using ITK to perform
> quantitative magnetic resonance perfusion analysis. In this project we
> use ITK's bilateral filter implementation to smooth the data before
> performing deconvolution. This is a very costly operation and takes a
> significant amount of time on the 4D data-sets that we work with.
> 
> Recently an article has been published regarding a fast bilateral
> filter implementation that performs significantly faster than other
> bilateral filter accelerations while maintaining accuracy. I would
> like to implement this algorithm as a class in ITK. As per the ITK
> submission guidelines, I am first mailing the developer mailing list
> to ensure that this has not already been implemented in ITK. I have
> also provided an abstract for more detail.
> 
> Sincerely,
> Jordan Woehr
> 
> 
> Abstract:
> 
> Currently a bilateral filter class (itkBilateralImageFilter) exists
> within ITK. This class implements the bilateral filtering algorithm
> proposed by Tomasi and Manduchi [1]. The bilateral filter smooths an
> image while not blurring its edges. However, it is computationally
> expensive and requires many multiplication and add operations per
> pixel. Paris and Durand proposed a fast approximation for the
> bilateral filter and have shown that their implementation is more
> accurate than other accelerations [2], but it has not yet been
> implemented in ITK.
> 
> The proposed class would implement the fast bilateral filtering
> algorithm for grey scale and color images. This would be achieved by
> taking the input image and organizing it into the required data
> structure. The ITK Image class is being considered as the container.
> The currently existing itkDiscreteGaussianImageFilter will then be
> used to blur the higher dimensional image. The discrete Gaussian image
> filter was chosen because the kernel width used should usually be
> small due to the down-sampling involved when using this technique [2].
> As described in the ITK documentation, this class should outperform
> the recursive Gaussian algorithm due to the small kernel size [3].
> After the Gaussian blur has been completed the data will be
> interpolated and written to the output image. By incorporating this
> class into the ITK framework, this more efficient algorithm can be
> made available for ITK users.
> 
> References:
> 
> [1] C. Tomasi , R. Manduchi, "Bilateral Filtering for Gray and Color
> Images," Proceedings of the Sixth International Conference on Computer
> Vision, p.839, January 04-07, 1998.
> 
> [2] S. Paris, F. Durand, "A Fast Approximation of the Bilateral Filter
> Using a Signal Processing Approach," International Journal of Computer
> Vision, vol. 81, no. 1, pp. 24-52, January 2009.
> 
> [3] Dimitri van Heesch, “ITK: itk::DiscreteGaussianImageFilter<
> TInputImage, ToutputImage > Class Template Reference”, [Online
> Documentation], (May 28, 2009), Available at HTTP:
> http://www.itk.org/Doxygen314/html/classitk_1_1DiscreteGaussianImageFilter.html
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