denoising.wavelets_mrtransform

class pywicta.denoising.wavelets_mrtransform.WaveletTransform

The wavelet transform wrapper for ctapipe.

clean_image(input_image, type_of_filtering='hard_filtering', filter_thresholds=[0.0, 0.0], last_scale_treatment='mask', detect_only_positive_structures=False, kill_isolated_pixels=False, noise_distribution=None, tmp_files_directory='.', output_data_dict=None, **kwargs)

Clean the input_image image.

Apply the wavelet transform, filter planes and return the reverse transformed image.

Parameters:

• input_image (array_like) – The image to clean.
• type_of_filtering (str) – Type of filtering: ‘hard_filtering’ or ‘ksigma_hard_filtering’.
• filter_thresholds (list of float) – Thresholds used for the plane filtering.
• last_scale_treatment (str) – Last plane treatment: ‘keep’, ‘drop’ or ‘mask’.
• detect_only_positive_structures (bool) – Detect only positive structures.
• kill_isolated_pixels (bool) – Suppress isolated pixels in the support.
• noise_distribution (bool) – The JSON file containing the Cumulated Distribution Function of the noise model used to inject artificial noise in blank pixels (those with a NaN value).
• tmp_files_directory (str) – The path of the directory where temporary files are written.
• output_data_dict (dict) – A dictionary used to return results and intermediate results.

Returns:

Return type:

Return the cleaned image.