Artificial Intelligence Technologies in Photo Correction

| Updated on September 26, 2024
AI Technology in photo correction

AI is playing a major role in almost every department. In photo editing, noble AI tools are helping in making minor editing features such as unblur images. The tech has now been able to manage editing on its own, with minimal manual efforts. 

In fact, AI tools are now a necessary commodity in the field. It has made the process much quicker and streamlined. Whereas there are numerous options to go for on the internet, the photo quality and other features like render speed, etc. must stay on the top. 

Diving deeper, this article is going to give you a deeper insight into AI technologies in the photo correction domain. Keep reading.

What is AI Photo Correction?

AI photo correction is all about making minor changes to the image with automation. Changes like removing the background, unblur or blur the image, etc. Along with automation, there are other practices as well like machine learning that help improve the functions further with time.

Not only editing, but the tech is also making noticeable changes in other domains like image generation and more. At the backend, AI photo editor tools incorporate numerous technologies. Let us tell you more about them.

The Key AI Technologies in Photo Correction

As previously mentioned, AI tools in photo correction seek help from various technologies. Here are the following:

1. Deep Learning and Neural Networks

Both deep learning and neural networks are subdomains of machine learning. Starting with deep learning, it’s all about recognizing and learning about the patterns in texts, images, and sounds. Whereas, neural networks are made replicating human brains. It learns and understands from the mistakes made by the program and improves them.

2. Convolutional Neural Networks (CNNs)

Being a neural network at its core, CNN is all about recognizing the patterns and understanding the behaviors. It finds the familiarity between the images, and with consecutive inputs, it keeps on upscaling its functions. 

3. Generative Adversarial Networks (GANs)

Tools like Image Upscaler utilize this technology to improve image quality. GANs can also be used for other tasks such as colorization, image inpainting, and super-resolution. They are simply made up of two neural networks: a generator and a discriminator. The generator creates the new data that seems exactly like the real data, and discriminates if the new data is real or fake.

4. Super-Resolution Imaging

As the name suggests, this technique is used to improve the resolution or quality of the image. The image resolution can be corrected through the optical or geometrical SR. The choice of technique completely depends upon the need.

5. Autoencoder Neural Networks

Whenever there’s a need for data manipulation, image recognition, dimensionality reduction, or any similar editing, Autoencoder Neural Networks come into focus. Interestingly, these are also a kind of neural network. 

DID YOU KNOW?
Today, just 15% of enterprises are using AI. But 31% said it is on the agenda for the next 12 months. (Source: Adobe)

How AI is Improving Photo Correction

 before and after image

With various advantages such as automation, quick rendering, etc. AI has made a noticeable change in photo correction. If you want to know more, refer to the following list:

  • Automatic Background Removal: Artificial intelligence is now intelligent enough to let the program make changes to the inputs by itself. So, now you do not have to mark the areas to remove, but, the AI can do that for you.
  • Enhanced Color Correction: In case the lighting or shadows in your picture are not good, let the AI handle it. It can make necessary adjustments like improving vibrancy, balance, and tone.
  • Automated Face Enhancement: AI is finally now able to detect and enhance the faces in the photos. With respect to the needed editing, it can play with the skin tone, reduce wrinkles, and enhance features.

Real-World Applications of AI Photo Correction

In the real world, implementing AI photo correction can be a bit tricky. Here is how you can start implementing them:

  1. Photography and Photo Editing: When taking photos or editing them, use AI at stages that can be managed by the program itself. For example, adjusting brightness, using filters, etc.
  2. Restoration of Old Photographs: If there’s any monochromatic photo or a photo from a really old camera, you can adjust its color with the help of AI.
  3. Social Media and Marketing: Social media marketing on platforms like Instagram, Facebook, etc. demand high-quality images. Especially for a business, posting low-quality, blurry images is a big loss. 
  4. Security and Surveillance: You can alter the colors and clarity of surveillance images from the CCTV or other security cameras. Everything can be managed by AI photo correction. 

DID YOU KNOW?
Consumers use more AI than they realize. While only 33% think they use AI-enabled technology, 77% actually use an AI-powered service or device.

The Future of AI in Photo Correction

The future of AI in photo correction is quite bright and the elevating significance of psychometric testing in evaluating skills and abilities suggests it. Since the tech is in high demand for almost every industry, photo and video correction are adopting AI for various roles. Apart from that, The following are some developments that we can expect from AI: 

  • Real-Time Editing: You will be able to see all the adjustments and editing happening in real-time.
  • Generative AI: The ability for programs to generate new images from the prompt will become easier and more efficient.
  • Ethical Consideration: With AI becoming more powerful, the regulations and ethical point-of-view will be emphasized.

Conclusion

Finally, AI in photo correction is in high demand. AI makes the whole process quick and automated. With its popularity, the programs are getting more efficient day by day. In this article, we also discuss the future prediction about AI in photo correction. Hence, if you find this article helpful, consider sharing it with your friends or peers.




Vaibhav Krishna

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