Image Cleaning¶
Cleaning/denoising of images (tailcuts cleaning, dilation, filtering).
An example of image cleaning and dilation:

API Reference¶
ctapipe.image.cleaning Module¶
Image Cleaning Algorithms (identification of noisy pixels)
All algorithms return a boolean mask that is True for pixels surviving the cleaning.
To get a zero-suppressed image and pixel
list, use image[mask], geom.pix_id[mask]
, or to keep the same
image size and just set unclean pixels to 0 or similar, use
image[~mask] = 0
Functions¶
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Clean an image by selection pixels that pass a two-threshold tail-cuts procedure. |
|
Add one row of neighbors to the True values of a pixel mask and return the new mask. |
|
Clean an image by selection pixels that pass a three-threshold tail-cuts procedure. |
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Clean an image by selection pixels that pass the fact cleaning procedure. |
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Identify all pixels from selection that have less than N neighbors that arrived within a given timeframe. |
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Extract all pixels that arrived within a given timeframe with respect to the time average of the pixels on the main island. |
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time constrained cleaning by MAGIC |
Classes¶
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Abstract class for all configurable Image Cleaning algorithms. |
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Clean images using the standard picture/boundary technique. |
Class Inheritance Diagram¶
