Working on Still Images You Generated
Some generative flaws are optical and some are structural. Only one of them is a sharpening problem, and telling them apart costs nothing.
Generated images almost always arrive softer than the model appeared to produce them. Part of that is the render itself, which frequently resolves structure only loosely; part of it is the export, where resizing and compression take whatever crispness existed; and part of it is that most people judge a generation in a grid view and then discover the flaws at full size. Enhancement addresses the first two kinds of softness, which is why it is worth 8 credits on a shortlisted render.
It does not address the third category at all. A misplaced finger, lettering that spells the wrong word, a pattern that stops halfway through a surface and a reflection that behaves wrongly are structural errors, and sharpening makes them more visible rather than correcting them — an eighth guitar string is still an eighth string with better edge contrast. Those belong back in the generator. When the render is structurally sound and merely soft, the sharpening pass is the right tool, and when the problem is that it lacks pixels rather than definition, that is the AI image upscaler.
What it does
Built for this specific job, not a generic editor.
Firm up soft renders
Loosely resolved surfaces, drifting outlines and elements that were never quite sharp become defined enough to use as a final asset rather than a draft.
Legibility for small elements
Signage, labels, logos and interface elements inside a generated scene improve at full size — but only where the shapes were roughly right. Wrong geometry gets sharper, not correct.
A defined cost relative to generating
The pricing page puts a generated image at 2 credits against 8 for an enhancement, so sharpening costs four times as much as producing another candidate. That ratio decides most of the workflow below.
The file stays in the workspace
Once a still is sharp it can move on to watermark removal or into video work without being exported and re-uploaded, which keeps further compression out of the chain.
How it works
Four steps, no timeline to learn.
Sort your rejects into soft and wrong
Zoom to 100 percent and decide which failure you are looking at. Softness is a sharpening problem; incorrect anatomy, broken lettering and nonsensical geometry are not, and no amount of processing turns them into usable detail.
Generate one more candidate before enhancing a bad one
At 2 credits against 8, another render is the cheaper option whenever doubt remains. Only spend the larger amount on an image whose structure has already been approved.
Export PNG, then run the pass
PNG and JPG are the accepted inputs and PNG is preferable. An estimated 10 to 25 seconds later you have a version to compare against the original at actual pixels.
Enhance once, at the end
Do not sharpen during iteration — you will pay repeatedly on files you discard and then sharpen the final version a second time. Resolve the structure first, then spend the 8 credits once.
What people use it for
The jobs this actually gets used for.
Thumbnails and cover art
A single generated image carrying a video or article, where it is viewed large enough that softness is immediately obvious and old.
Concept stills for a pitch
Generated scenes that need to look deliberate in a deck, where visible softness reads as carelessness rather than as a stylistic choice.
Product and packaging mockups
Generated mockups whose label text and material edges need to hold up when a client zooms in during a review.
Shortlisted frames from a large run
Hundreds of cheap generations filtered down to a handful worth finishing, with the cost of polishing each one worked out in advance.
Why sharpening will not fix a mistake the model made
One problem is missing detail. The other is a wrong decision, and they are not adjacent.
Generated imagery produces two distinct classes of flaw, and confusing them is how credits get wasted. The first is optical: genuinely low local contrast, soft edges and surfaces that were never resolved, which is precisely what a sharpening pass is designed for. The second is structural: a limb in the wrong position, a word spelled wrongly, a pattern that collapses into noise, a reflection that contradicts its light source. Those are decisions the model made, and no pixel-level operation revises a decision.
The cost structure points the same way. A generation costs 2 credits according to the pricing page’s own conversion, and an enhancement costs 8. So sharpening is four times more expensive than simply asking for another candidate, and it is only the sensible purchase once the content itself has been approved. Rushing the price paid for fixing something that a fresh render would have fixed by chance is a common and expensive habit.
That gives a simple ordering. Generate several variants, reject the ones that are structurally wrong regardless of how soft they look, choose among the rest, export the winner as PNG and sharpen it exactly once. Done the other way round — sharpening during exploration — every discarded file pays the higher rate, and the image you finally keep has been through the workflow twice.
Credits and plans
Every tool draws on one shared credit balance.
Enhancing one image costs 8 credits, against 2 credits for generating one, with an estimated 10 to 25 seconds of processing per run. Free provides 30 credits monthly with no card — three enhancements, or fifteen generations — and includes commercial use with no watermark on exports, one task at a time at standard speed. Starter is $9 for 400 credits and two parallel tasks; Pro is $19 for 1,000 credits, three tasks and a priority queue; Studio is $59 for 4,000 credits, six tasks and API access.
Related guides
Longer reads on the same workflow, from the OpenFilmo blog.
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Related tools
Closely related pages on the same problem.
Frequently asked questions
How expensive is this compared with just generating another image?
Four times a generation. The pricing page converts 30 credits into fifteen generated images, putting one at 2 credits, while an enhancement run costs 8. That ratio is why generating another candidate is usually the better first move.
Which formats does the enhancer take?
PNG and JPG. Export from your generator or editor into one of those first, and prefer PNG, since re-saving as JPG adds compression artefacts that the pass then treats as detail.
Will it fix hands, spelling or other generation errors?
No. Those are structural errors and sharpening has no opinion about them — it will make a wrong spelling crisper rather than correct. Regenerate instead; at 2 credits a new candidate is cheaper than any repair attempt.
Can I publish the enhanced result commercially?
Yes. Commercial use is included on the Free plan and on paid plans, and exports carry no watermark. Check the labelling requirements that apply to generated content in your market before publishing.
Should I upscale my generated image instead?
It depends on the complaint. If it needs more pixels — a print, a 4K frame or a marketplace size requirement — the AI image upscaler is the right tool. If it has the pixels but shows them softly, sharpen here. Fast Enhancer lists upscale and sharpen together but publishes no factor, so do not budget a specific output size around it.
More OpenFilmo tools
Other generators and utilities in the same workspace.