vista.algorithms.background_removal.robust_pca.run_robust_pca

vista.algorithms.background_removal.robust_pca.run_robust_pca(images, lambda_param=None, tol=1e-07, max_iter=1000, callback=None)[source]

Apply Robust PCA background subtraction to a 3D array of images.

Parameters:

  • images (ndarray) – 3D numpy array (num_frames, height, width) containing image data

  • lambda_param (float, optional) – Sparsity parameter, by default auto = 1/sqrt(max(m,n))

  • tol (float, optional) – Convergence tolerance, by default 1e-7

  • max_iter (int, optional) – Maximum iterations, by default 1000

  • callback (callable, optional) – Optional callback function called after each iteration. Called with (iteration, max_iter, rel_error). Should return False to cancel processing.

Returns:

(background_images, foreground_images) where:

  • background_images: Low-rank background component (same shape as input)

  • foreground_images: Sparse foreground component (same shape as input)

Return type:

tuple of (ndarray, ndarray)