Debunking 6 Common Myths Surrounding AI Image Enhancement
AI image enhancement tools seemingly came out of nowhere but show no signs of slowing.
The AI image enhancement market is expected to be valued at over $5 billion by 2033.
AI image enhancement has garnered several myths on its short but rapid climb to the top — these range from somewhat true to completely false.
Let’s dive into the world of AI image enhancement and debunk 6 of the most common myths surrounding this new technology.
What is AI image enhancement?
AI image enhancement uses AI algorithms to improve image quality and colors immediately. By analyzing your image, this technology can:
- Enhance resolution;
- Improve color balance;
- Increase sharpness;
- Reduce noise;
- Add generated elements;
- Restore old and faded imagery.
AI image enhancement tools of all shapes and sizes are arriving every day in this rapidly evolving ecosystem.
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Debunking 6 myths around AI image enhancement
#1. AI can fix any bad images
AI image enhancement can improve aspects of your image. However, AI can’t yet restore details that are missing in the original image. This can be due to:
- Extreme blurriness;
- Severe distortion;
- Over or under exposure;
- Broken pixels.
While the technology can predict these missing details, AI has real trouble with understanding context — the results are often far from optimal.
#2. AI enhancement is better than human editing
As soon as this technology hit the shelves, users made claims that it had surpassed human editing abilities. While it’s possible in the future, present AI image enhancement tools can’t compare to a human editor.
For now, there are a few things AI can do better:
- Improving image resolution;
- Quickly adjusting color balance;
- Instant image generation.
Yet, when it comes to important details like context, creative vision, visual metaphors, and textures, the human touch is unrivaled, for now…
#3. AI enhancement is always easy
Since the AI boom began, companies have been claiming things like “one-click solutions” and “no prior knowledge required”. When it comes to high-quality AI image enhancement, this is not necessarily the case.
Effective usage of these tools requires some technical knowledge and often multiple enhancement rounds. Manual adjustments may need to be made to remove artifacts and achieve natural-looking results.
#4. AI creates lifelike imagery
Don’t get me wrong — AI-generated images are producing more detailed and realistic images by the day. However, upon close inspection, the touch of AI is easy to see. Details that are often askew are:
- Details of hands and faces;
- Unnatural shadows or reflections;
- Unrealistic hair textures.
These inconsistencies, when viewed closely, break the AI’s illusion of realism. For now, photography and human painting are superior to realism.
#5. AI image enhancement only works with photography
Unlike what you may have heard, AI image enhancement covers far more than just photographic editing. In addition to photography, AI can also enhance:
- Digital art;
- Hand-drawn or digital illustrations;
- Scanned documents;
- Outdated video-game visuals.
Artists in various fields can take advantage of this breakthrough technology to enhance anything from old comic books to faded historical documents.
#6. AI will replace human artists
Since its inception, generative AI has carried the myth that it will eventually replace all writers, painters, photographers, etc. However, this is probably one of the biggest AI myths being circulated.
It’s well-known that AI succeeds at repetitive, time-consuming tasks. What it makes up for in speed it lacks in creativity and narrative vision. When it comes to expressing deeply human emotions, AI image enhancement just can’t compete.
Facing the limitations of AI image enhancement
Every new technology has its own set of limitations, and AI image enhancement tools are no different.
The reliance on good image quality
It’s super simple — the more data the AI has to work with, the better the results. Low-resolution, blurry, or overexposed images are lacking huge amounts of data. The AI can attempt to fill the gaps, but it will most likely fail.
AI’s inability to read context
At the core, when AI image enhancement fails, it’s likely due to a misunderstanding of context. AI has a hard time predicting this, so it makes a guess. Without context, it’s impossible to recover or restore missing image data.
The role of AI bias
Inherent AI bias is often overlooked when discussing the limitations of AI image enhancement. AI are trained from databases — if they’re too small, non-inclusive, or simply inaccurate, the AI will be biased and unable to produce accurate results.
Conclusion
AI image enhancement has drawn the gaze of artists of all kinds. Due to its provocative nature, AI enhancement tools have gathered quite a few myths in their short lifespan.
While it’s not always a one-click solution, this technology excels at high-quality image adjustment but falls short when reading context.
How would you use AI image enhancement tools?
