Neural Image classifier networks are a very emergent technology and although incredible in what they’re able to achieve, still have some limitations.
For instance, where a low resolution image is up-scaled, the AI attempts to do its best at filling in areas of missing data by comparing what it’s seeing to what should be there. It then makes a best guess estimate at filling in those blanks with new data it generates itself. Sometimes this can result in a shimmery, ‘water-color painting’ effect that although higher resolution does look a little computer generated compared to the original. Most of these trade offs however are offset by the increased resolution and general tidying up of the image.
Removing noise from an image is generally quite effective however sometimes the AI can erroneously smooth areas that it should not touch and also leave things that it should have removed. It is however true to say that 95% of the time the net sum is a marked improvement over the original.
It is important to be aware of these quirks before engaging Trender to AI process your images and video footage. We will always endeavor to generate the best output quality but there are some inherent technological limitations that at the time of this writing cannot be fixed.