AI SEO Weekly

SEO Image Optimization

By @ValeIzzo86 & @CyberAndy

Improve your schema markup with super-resolution images

What is Super Resolution for images?

What is Super Resolution for images?

It's a technique to enlarge and enhance your website images and improve structured data markup using a state-of-the-art deep learning model.

How Super Resolution works

How Super Resolution works

Start from a single low-resolution image (original) and scale it up to get a high-resolution image that retains the original details by using AI.



To replace the missing details, the network will make a guess about which pixel will go to which position.

Why Do You Need Hi-Resolution Images In SEO?

Why Do You Need Hi-Resolution Images In SEO?

Google needs large images in multiple formats to present your content in carousels, tabs (rich results on multiple devices) and Google Discover.

How can you improve the user's image experience?

How can you improve the user's image experience?

Add structured data to your content and be sure to follow these important recommendations: 


- One image for each piece of content - Images can be crawled and indexed by Google - Images are representative of the marked up content

- Use a supported file format - Use multiple high-resolution images - Use aspect ratios: 16×9, 4×3, and 1×1

WordLift does it all for you🤩 But...

You need to have at least 1.200 pixels on the shortest side of your image🤔

You don't have that... don't worry, we have the solution... and it is FREE!

1.  Set up the environment 2.  Load the files (you can upload a folder or a list of URLs) 3.  Download the processed files

It will check the size of the image before processing it (no waste energy if you don’t need)

It provides the option to apply image compression after the upscaling

In only a few days we could immediately spot the treated URLs appearing in the recipe carousels 🎉.

Happy upscaling and don’t forget that you can use machine learning also to automatically describe the content of your images as shown in this tutorial 👀