Clean Image Set

The Clean Image Set command identifies and repairs random image artifacts caused by a cosmic rays and ionizing radiation events that appear at a given location in one image but not another. This command works on a displayed Image Set. The artifact coordinates may be saved to a text file or listed in the Main Message Pane, where they may be copied or opened into a text editor. If the Message pane is closed, use the Windows > Main Messages command to open it.

Example: See the Tutorial: Cleaning Artifacts from an Image Set.

The Clean Image Set command opens from the Image Window > Process > Calibration menu when an Image Set is displayed in the top-most window.

Since this command often works with a large Image Set "undo" backup copies are not automatically created, for the purpose of reducing memory usage. If you want Undo copies, tick the Create Undo copies of images checkbox.

Overview of the Method

The Clean Image Set algorithm detects random "events" that appear at the same location in only 1, 2, or a few images of a large collection of images of the same field of view. The algorithm uses the pixel information from a series of images to identify the artifacts in each of the individual images. Therefore, this command works only on an Image Set made from multiple images of the same field of view. To separate artifacts from persistent features, the images must be aligned through the image set. If an image set is registered in software before cleaning, poorly corrected hot or cold pixels shift around, causing the algorithm to detect them the same as true radiation events.

This algorithm detects outlier pixel values by comparing them with a statistical model based on information from the entire image set. This has advantages over other methods commonly used to reduce outlier noise from radiation events: Most cosmic ray detection algorithms use information from neighboring pixels within a single image. The weakness of such methods is their difficulty in distinguishing outliers from sharp persistent features such as the peaks of stars. Conversely, standard image combining techniques using rejection methods such as Sigma Clipping, Alpha Clipping, or the Median, can remove outlying pixels as part of merging, but end up producing a single image (see Statistical Estimators for Image Combining). One weakness of rejection methods is that the Signal to Noise Ratio ("SNR") is lowered in comparison with simple Mean combining, either as a result of rejecting ("clipping") pixels or by the nature of the Median process itself. the median reduces the SNR of all pixels by about 20%. In comparison, the present algorithm attempts to modify only the true outlier pixels and does so in the individual images without actually combining the images. This algorithm requires that the image features (not the defects) are aligned so that a statistical model can by built for pixel variations within the image set. If the images require alignment, several tools are available, including the Image Registration package, the Align by WCS, and the Align on Point commands. When registering images, consider choosing the nearest neighbor resampling option to preserve the noise structure within each image.

Note:

This method will detect a variable object or transient object as an "event" and reject it from the images. Do not use this method if the image set contains an important object or feature that is significantly varying in position or brightness between the images.

Clean Image Set Properties

Profile	Selects the parameter profile for this command and allows you to save or work with existing presets.
Image Set to be Cleaned	Select the Image window containing the image set to process. This command only works with image sets and the list is updated as each new image window is created, so be sure the target image window you want to process is selected.
Statistical Aggressiveness	Controls the statistical cutoff for the probability that an outlier pixel is actually a bad pixel. A lower setting rejects pixel values that are more deviant from the others and a higher setting rejects pixels that are less deviant from the others.
Sigma Rejection Strength	Controls whether more or fewer outlying values are rejected and whether they are rejected symmetrically about the mean.
Pixel Repair Method	Select the method to apply to the detected outlier pixels. The Replace with Zero method replaces the outlying pixels with a value of 0 for combining using the "Mean - Masked by 0" method.
Create Undo copies of images	Check this box to create Undo copies of the image set, You can then use the Undo (Ctrl+Z) command to recover the original images, perhaps to try a new selection of Properties. Not using this method helps conserve memory if you are combining a large set of large images which use most of the available memory.
Save rejected pixels to a file	Check this box to save the results to a text file. This is the same information saved to the Main Message pane if List rejected pixels is checked.
List rejected pixels	Check this box to list the coordinates of the rejected pixels. The listing uses a format compatible with Pixel Masks. This is the same information saved to a text file if Save rejected pixels to a file is checked. The processing summary and pixel listing is sent to the Main Message Pane. If the pane is closed, open it using the Windows > Main Messages menu command. Note that a large number of artifact coordinates (e.g., more than 10,000) may take a while to list in the message pane.
Display rejection map image	Check this box to display an image showing the rejected pixels. The image has a zero background and is encoded with a value that corresponds to the sequence number of the image where that pixel was rejected. For example, a pixel value of 3 means that the pixel was rejected from the 3rd image of the image set.

Overview of the Method

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