Deconvolution: Detail Recovery from Seeing-Limited Data
StarTools' Deconvolution module allows for recovering detail in seeing-limited data sets that were affected by atmospheric turbulence.
The Deconvolution algorithm in StarTools is so fast, that previewing and experimentation to find the right parameters can be done in near-real-time.
The Deconvolution module incorporates a new regularization algorithm that automatically finds the optimum balance between noise and detail and puts you in control of this trade-off in an intuitive way.
A novel de-ringing algorithm ensures stars are protected from the Gibbs phenomenon (also known as 'panda eye effect'), while actually being able to still coalesce singularities like over exposed white cores of stars into point lights. You have full control over your de-ringing mask during the operation (not just before).
Creating a suitable de-ringing mask that works very well in most cases, is done in a single click!
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- Bin: Trade Resolution for Noise Reduction under Modules
Similarly, deconvolution (and subsequent recovery of detail that was lost due to atmospheric conditions) may not be a viable proposition due to the noisiness of an initial image.
- Usage under AutoDev
AutoDev finds the best compromise global curve, given what detail is visible in your image and your preferences.
- Flux: Automated Astronomical Feature Recognition and Manipulation under Modules
Knowing which features probably represent real DSO detail, the Fractal Flux is an effective de-noiser, sharpener (even for noisy images) and detail augmenter.