Improved internal memory controls (much more stable and faster on big datasets), fixed CPU image viewer, fixed Narrowband extraction demosaic algortihms.
New improved Normalization engine, Fixed random crashes in integration, fixed RGB Combine & Calibrate Star Colors, fixed Narrowband extraction algorithms, new development platform with performance gains, bug fixes in the tools, etc...
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Update on the 2.0.0 release & the full manual
We are getting close to the 2.0.0 stable release and the full manual. The manual will soon become available on the website and also in PDF format. Both versions will be identical and once released, will start to follow the APP release cycle and thus will stay up-to-date to the latest APP version.
Once 2.0.0 is released, the price for APP will increase. Owner's license holders will not need to pay an upgrade fee to use 2.0.0, neither do Renter's license holders.
[Solved] Interpolation artifacts with Lanczos, Catmull-Rom Spline, Mitchell-Netravali, Cubic B-Spline
I'm getting little bit of interpolation artifacts for the data set that I'm working with.
There are dark pixels at the edge of some stars when I use Lanczos-3 as the interpolation algorithm.
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In fact the artifacts are a lot worse in Pixinsight.
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They are much less noticeable with APP.
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If I use bilinear algorithm, the artifacts go away but the image is not as sharp as one from Lanczos-3(bigger FWHM value).
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I'm wondering if there is a way to preserve FWHM but remove the artifacts.
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Thank you very much.
Donghun
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Hi Donghun,
Yes, I clearly see the artefact. This artefact is known as undershoot. This will always happen with a data interpolation algorithm like Lanczos.
But there is a solution to prevent this in APP. You will need to enable the "no under/overshoot" selectbox below the pixel interpolation filter in 6) INTEGRATE. This should prevent these dark pixels at the star borders due to undershoot.
Let me know if this solves the artefacts with your data.
Mabula
Under and Overshoot happens because a filter like Lanczos has positive and negative lobes see:
