I am always amazed to see how many people are actually using this script. I never expected this to happen.
- The script can be used in a batch fashion on many images. 1. Define your parameters, and use the blue triangle to drag the instance to your workspace. 2. Use ImageContainer to define all the images to which you want to apply it. 3. Drag ImageContainer to instance on workspace. I used this procedure to create some timelaps videos.
- I usually apply it to a single image after calibration, before further processing. This has the advantage that image defects are easier to distinguish from (patterned) noise than in images not yet integrated. Also, it requires application to only one image instead of the whole stack. On the other hand, at this point in time, image defects have already spread over larger regions and may have been rotated due to alignment+integration, and may have spread to neighboring pixels/other color channels due to debayering.
- I am not sure if application to calibrated CFA images (not yet debayered, aligned, stacked) has a benefit. On the positive side is that defects have not yet spread due to debayering, alignment, integration. In the negative side is the low SNR of those frames. We would need to test. It is not yet possible with the current script, because it cannot handle CFA images.
- Same for application directly to the RAW files (dark, flat, bias+light). In theory, this may improve the results of the calibration process because it would remove an unwanted noise source. We would need to test. It is not yet possible with the current script, because it cannot handle CFA images.
It makes a lot of sense to translate this script into a proper module:
- Proper "blue triangle" functionality. While dragging to the desktop works fine, the entry in the processing history of an image only records the default parameters, not those actually used.
- Speed. C++ should be much faster the PJSR
- It may be possible to integrate the module with the proper Realtime Preview feature of PI
- While working on it, one may want to add additional functionality:
-- work on horizontal and vertical banding (not sure if arbitrary angles make sense)
-- direct work on CFA image. I think that a solution handling CFA images as four channels (2 green channels) would be sufficient-it would not even need to know the actual Bayer pattern. The Bayer pattern may be required to support proper preview.
-- (optionally) separate parametes for each channel (I find that red has significantly different noise characteristics the G or B.)
If someone wants to work on it or translate to PCL, feel free to do so - I would be glad to see it improved. Just leave it under a free open source license compatible with PI (e.g. BSD), and mention the parents (Jens Dierks, the author if Fitworks (http://www.fitswork.de/software/impressum.php
) who permitted reimplementation of this functionality based on his program, and myself) in the copyright message.