pysteps.motion.proesmans.proesmans

pysteps.motion.proesmans.proesmans(input_images, lam=50.0, num_iter=100, num_levels=6, filter_std=0.0, verbose=True)

Implementation of the anisotropic diffusion method of Proesmans et al. (1994).

Parameters:

input_images : array_like

Array of shape (2, m, n) containing the first and second input image.

lam : float

Multiplier of the smoothness term. Smaller values give a smoother motion field.

num_iter : float

The number of iterations to use.

num_levels : int

The number of image pyramid levels to use.

filter_std : float

Standard deviation of an optional Gaussian filter that is applied before computing the optical flow.

verbose : bool, optional

Verbosity enabled if True (default).

Returns:

out : ndarray

The advection field having shape (2, m, n), where out[0, :, :] contains the x-components of the motion vectors and out[1, :, :] contains the y-components. The velocities are in units of pixels / timestep, where timestep is the time difference between the two input images.

References

[PGPO1994]