Photographs help us preserve events in time. They don't just help us relive memories but also provide insights into important events from the past. Until color photography became mainstream, our photographic history was captured in black and white. The task of image colorization is to transform a given grayscale image into a plausible color version.

The task of image colorization can be undertaken from different perspectives. The manual process is very time-consuming and requires amazing skills (see the r/Colorization subreddit at https://www.reddit.com/r/Colorization/). Researchers in the field of computer vision and deep learning have been working on different ways of automating the process. Through this chapter, we will work toward understanding how a deep neural network can be leveraged for such a task. We will also try to utilize the power of transfer learning to improve upon the results.

We encourage readers to give the problem statement a thought before proceeding. Think about how you would approach such a task. Before we dive into the solution, let's get some information about color images and associated concepts. The following section covers the basic concepts required to work on the task at hand.