gjdonatiello
Affinity by Canva: First Impressions
Affinity by Canva: First Impressions
Credit: Giuseppe Donatiello
I spent half an hour learning/evaluating Affinity by Canva.
It's not an intuitive software, especially for those who aren't very experienced with editing, but it quickly makes you realize it's not one of those toy apps. Affinity is powerful, however, and includes a wealth of editing and graphics tools on par with more well-known and very expensive software.
It's not a product for astrophotography, so its value can be best demonstrated by its performance on non-ordinary images.
I limited myself to the Pixel section, i.e., photo editing, and after some testing, I ventured into processing a raw TIFF image of M42 (box 1), a subject rich in nuances, tones, and a myriad of details.
Even with the basic settings (box 2), the result is very satisfying. However, it's by exploring the advanced tools that I discover extremely useful applications for astrophotography, such as generating false-color images (box 3) and applying powerful and incredibly simple deconvolutional algorithms.
The use of deep learning in many tools is all too evident, and it's important/recommended not to get too carried away. The experienced user will know how much to use and, above all, when to stop to avoid entering the minefield of overprocessing, which is unfortunately widespread, where artifacts are considered objective details.
For software that has become free, can you expect more?
M42 taken with 127EDmm f/9
Affinity by Canva: First Impressions
Affinity by Canva: First Impressions
Credit: Giuseppe Donatiello
I spent half an hour learning/evaluating Affinity by Canva.
It's not an intuitive software, especially for those who aren't very experienced with editing, but it quickly makes you realize it's not one of those toy apps. Affinity is powerful, however, and includes a wealth of editing and graphics tools on par with more well-known and very expensive software.
It's not a product for astrophotography, so its value can be best demonstrated by its performance on non-ordinary images.
I limited myself to the Pixel section, i.e., photo editing, and after some testing, I ventured into processing a raw TIFF image of M42 (box 1), a subject rich in nuances, tones, and a myriad of details.
Even with the basic settings (box 2), the result is very satisfying. However, it's by exploring the advanced tools that I discover extremely useful applications for astrophotography, such as generating false-color images (box 3) and applying powerful and incredibly simple deconvolutional algorithms.
The use of deep learning in many tools is all too evident, and it's important/recommended not to get too carried away. The experienced user will know how much to use and, above all, when to stop to avoid entering the minefield of overprocessing, which is unfortunately widespread, where artifacts are considered objective details.
For software that has become free, can you expect more?
M42 taken with 127EDmm f/9