Synthetic Media - Image Synthesis

Image Synthesis is a branch of synthetic media where images are generated fully or partially using computing techniques and not using a camera lens. These images are not natural and are created using algorithms, models, or AI tools. Synthetic Image are used in various fields like entertainment, advertising, and even scientific research. In this section we will explain synthetic images, it's types, AI generated synthetic images and examples of synthetic images.

Types of Synthetic Images

With advancement in technologies different tools for creating artificial images were developed. Following are types of synthetic images used in different decades.

• Pixel Edited Images: During 1980s image editing tools like Photoshop become popular that can be used to alter pixel of natural images. This was first instance of synthetic image generation.
• Computer-Generated Imagery (CGI): By 1990 movies and video games started using computer-generated imagery which provided realistic visual effects.
• AI Image Generation: Currently artificial intelligence have advanced to generate completely new images based on human prompts.

Synthetic Images Using AI

AI algorithms are trained on large set of natural images to make them able to create new ones that look real. This process uses techniques like deep learning and neural networks. With AI, we can generate images of people, animals, and objects that dont exist in real life but look very realistic.

Example 1

Following image is an example of image generation using openAI's GPT 4.o

Example 2

Following image is an example of image generation using Google's imaGen-3

How AI Image Generators Work?

AI Image generators function by using complex machine learning algorithms and techniques. Here is step-by-step overview of this process.

• Training on Datasets: AI image generators are trained using large datasets of images. The AI learns patterns, styles, and features from these images to understand how to create new ones.
• Understanding the Text: The model then use NLP techniques to understand the meaning of the text prompts from user. It breaks the sentence down into semantic components to understand the objects and their relationship.
• Generative Adversarial Networks: The model uses Generative Adversarial Networks (GANs) which have generator and discriminator layers. Generator layer build image and discriminator layer fixes errors in images that generator build.
• Feedback Loop: The output generated will go through multiple feedback loops to ensure that the generated image closely aligns with the text description.

Synthetic Image Generation Tools

There are many tools available for creating synthetic images. Some popular ones include:

• DALLE: A model developed by OpenAI to generate realistic and artistic pictures images from written descriptions.
• ImaGen 3: A model developed by Google to create images based on specific styles or scenes, with more control over the look of the image.
• Midjourney: A tool that creates artistic and creative images from text, often used for unique and imaginative designs.
• Stable Diffusion: A tool that makes high-quality images using less computer power compared to other models.
• Deep Dream: This is also another tool from Google that turns normal images into strange, dream-like pictures using patterns from a neural network.