Short DescriptionCell membranes appear as structures of co-dimension 2, and suffer from discontinuities in intensity and orientation. Anisotropic PDE-based approaches offer an elegant solution to these problems, by integrating spatial and orientation information in a flexible and robust manner. In this work we propose a new tensor-based anisotropic model specifically adapted to 2D planar structures able to perform noise reduction and contrast enhancement simultaneously. REFERENCE: S. Pop, A. Dufour, J.-C. Olivo-Marin "Image filtering using anisotropic structure tensor for cell membrane enhancement in 3D microscopy" IEEE International Conference on Image Processing, Proceeding of ICIP2011, pp. 2085-2088, Bruxelles 2011
Input: 3D or 4D sequence (1 color channel)
Output: filtered sequence
Iterations: number of iteration for the computation. Higher value gives more filtered data.
Sigma: size of 1st Gaussian kernel (local filter)
Ro: size of 2nd Gaussian kernel (integration scale for the structure tensor); higher values can generate false structures around membrane
Z/X ratio: ratio between the depth (Z) resolution and the XY resolution
K PM: threshold for Perona Malik filter (advice: keep 5) higher value gives more isotropic effects
Threshold: important parameter which select the 1D and 2D behavior of the filter. It's the threshold for the fuzzy selection function.
4D stack: select this option only if you want to process a 4D stack with multi thread option
No threads: number of thread. one thread is applied on one time-stack. May create out of memory errors.