Real-World Applications of AI in Photography and Editing Software

The recent years have seen cameras increasingly edging towards what seems to be the limit, especially in terms of hardware. As photography technology advances fast, each achievement is groundbreaking for only a few months, or a year until another hit.

To make up for hardware limits and also complement the physical features of the camera, engineers have found artificial intelligence worthy. And smartphones have been at the forefront of this, as they try to obscure their physical limitations and catch up with DSLR cameras.

Nowadays, photography is more about algorithms than sensors and lenses, and today’s top cameras (especially in smartphones) are rated according to the power of AI backing them. And this growth is not limited to cameras alone but also extend to photo editing software for beginners or experts. These rapid developments mean a lot for different aspects of photo processing.

Photo Management

AI has increasingly helped to simplify the process of managing photos. Smartphones have made all of us at least amateur photographers. Human beings continue to break the record of the number of photos taken, but that poses another problem of easily managing photos.

Thankfully, many companies, with leaders being Google and Apple, have varying but similar technologies for easy photo management using machine learning.

• Google Photos uses machine learning to identify, tag and categorize several images in one swoop to ensure you have neat albums. Now, you can identify and isolate photos containing a dog, or even ones with a smile. It can also identify duplicates and remove them and also turn your images into GIFs. It works by supervised learning: machine learning to set up a collection of deep neural networks. This algorithm gets better with continual use.
• Similarly, Apple’s photo search feature builds on the same smart photo organization framework, though with more focus on privacy.

With such photo management apps, you can easily sort your photos and filter out the ones with bad quality.

Photo Editing

Machine learning in photography is seeing a rise of easy photo editing software to make image editing accessible for everyone and not just pros. There are many AI-inspired photo editing software for beginners with the advent of one-tap retouches that give photos a whole new look. There are many software to edit photos out there now giving beloved Photoshop a run for their money.

• Skylum is a top photo editing software that has an AI-powered upscaling that increases resolution. The result is sharper images at photo printing.
• Skylum also recently released Photolemur, an image editor that enables people to retouch photos automatically with one tap.
• Also, Meero uses AI for smart editing such as tone and color corrections, geometric correction, high dynamic range fusion, etc.
• Prisma Lensa is an easy photo editing software that has been dubbed the ‘one-button photoshop’. Its AI-powered approach to photo editing easy displaces many of the now popular ‘beauty filter’ apps.
• IN MEDIAKG TI has also released Fotoworks XL, a photo editing software that comes with an automatic image enhancing features that can transform your image. The feature allows you to get rid of imperfections and show the best sides of your photograph.
• With the Luminar app you can edit a photo using only slider to adjust features such as luminosity, saturation, white balance and contrast.

Hardware Processing

Smartphones are really limited, with regard to hardware capabilities, compared with DSLR cameras. They try to bridge this gap with AI. Different smartphone companies have announced more powerful processors, and smarter too, to handle images. From multiple cameras to smart processors, the trend in smartphone photography is to incorporate algorithms with hardware. And it has worked.

• Apple’s release of the A11 bionic neural engine chip was record-breaking. Using machine learning, it makes for better enhancement of images and more accurate image recognition, along with the capacity for AR. The current 8-core A12 bionic chip improves upon its predecessor, outperforming it several times more while giving pictures more depth among several features. Besides, the A13 will be released this year and it can only be better.

• Huawei’s Honor View 20 comes with a whopping 48 megapixels camera for capturing high-resolution images. It uses Sony’s IMX586 image sensor for this. The results include clearer pictures and high-res pictures that can be zoomed several times. Since its release, many other smartphones have tried to copy and improve upon the technology.
• Google’s Pixel is not left out too. Pixel 2 phones came with an image enhancement chip. Pixel 3 phones have a better version of this.
• 3-D sensors have become a thing too with chip vendors such as Lumentum locked in a race to get ahead.

Making algorithms work alongside smaller camera sensors such as is found in drone cameras and security cameras can be used to higher resolution surveillance pictures/videos and improve on security.

Image Recognition

Image recognition using machine learning is not new but it is growing more advanced.

• Apple’s Portrait mode with dual-camera iPhones was the first of many as it brought image recognition to real-time picture-taking. One camera is used to identify objects and people in a picture while the second camera gives the image depth and blurs the background. Since its release, many companies have adopted it for their smartphones too and it is one of the ways in which smartphone cameras are rivaling DSLRs.
• The Excire software is an advanced automatic object-tagging photo editing software that can identify people across age-groups and even nationalities.
• Recently, Canon partnered with researchers from the Technical University of Munich, Germany to artificially create background scenes even when obstructed by objects. The layered depth image technology uses Generative Adversarial Network (GAN) to infer backgrounds and construct them. Amazing!
• There are many phones like Huawei’s P20 Pro which has three back cameras for better image processing. It can recognize up to 500 scenes across 19 categories.

Photo Optimisation

Companies have focused on producing cameras capable of taking higher resolution pictures, but that translates to an increase in file size. While saving images to the cloud with apps like Google Photos and iCloud have worked, there is more that can be an is being done.

• Apple recently introduced the High-Efficiency Image Format (HEIF) on iOS 11 to rival mainstream photo formats like JPEG. HEIF boasts of high-quality pictures at the reduced file size and can help tackle the problem of limited storage space.

• Skylum has also been working on compressing several pictures at a go without compromising quality. Its AI research lab is handling this.

Conclusion

The above are only select examples of ways AI has impacted photography, and positively. The photo editing software for Windows 10 niche appears to be the biggest gainer in the AI revolution. It seems smartphones are trying really hard to catch up with DSLR cameras with innovative photo effects. DSLR cameras are not going out of vogue any time soon, especially for pros. But there is still much potential in mobile photography powered by AI.