Anisotropic Smoothing

def curvature_anisotropic_diffusion_image_filter(input, number_of_iterations=5, time_step=0.0625, conductance_parameter=3.0):
    """
    Curvature-based anisotropic diffusion.
    
    Parameters:
    - input: itk.Image - Input image
    - number_of_iterations: int - Number of diffusion iterations
    - time_step: float - Time step (must satisfy stability criterion)
    - conductance_parameter: float - Controls sensitivity to edges
    
    Returns:
    itk.Image - Smoothed image with preserved edges
    """

class CurvatureAnisotropicDiffusionImageFilter:
    """Edge-preserving smoothing using curvature-driven diffusion."""
    
    def SetNumberOfIterations(self, iterations):
        """Set number of diffusion iterations."""
    
    def SetTimeStep(self, time_step):
        """Set time step for diffusion."""
    
    def SetConductanceParameter(self, conductance):
        """Set conductance (edge sensitivity)."""

def gradient_anisotropic_diffusion_image_filter(input, number_of_iterations=5, time_step=0.0625, conductance_parameter=3.0):
    """
    Gradient-based anisotropic diffusion.
    
    Parameters:
    - input: itk.Image - Input image
    - number_of_iterations: int - Number of diffusion iterations
    - time_step: float - Time step
    - conductance_parameter: float - Controls sensitivity to edges
    
    Returns:
    itk.Image - Smoothed image
    """

class GradientAnisotropicDiffusionImageFilter:
    """Edge-preserving smoothing using gradient-driven diffusion."""

class VectorCurvatureAnisotropicDiffusionImageFilter:
    """Anisotropic diffusion for vector images."""

class VectorGradientAnisotropicDiffusionImageFilter:
    """Gradient anisotropic diffusion for vector images."""

import itk

image = itk.imread('noisy.png', itk.F)

# Curvature anisotropic diffusion
smoothed = itk.curvature_anisotropic_diffusion_image_filter(
    image,
    number_of_iterations=10,
    time_step=0.0625,
    conductance_parameter=3.0
)
itk.imwrite(smoothed, 'anisotropic.png')