Colorization is the process of adding colour to black-and-white or monochrome images, transforming grayscale content into full-colour representations. Historically, this was a painstaking manual process requiring artists to hand-paint colour onto each frame or image, but modern AI tools have made colorization a largely automated, high-quality workflow accessible to anyone working with archival or historical imagery.

AI colorization models are trained on vast datasets of colour images and their corresponding grayscale versions, learning the statistical relationships between luminance patterns and likely colours. The models make educated guesses about what colours were most likely present based on context, texture, and object recognition. Skin tones, skies, vegetation, and other common elements tend to be colourized accurately, while ambiguous objects such as clothing or interior design elements may be assigned plausible but not necessarily historically accurate colours. Advanced models allow users to guide the colorization process with hints or reference images to improve accuracy.

For creators working with archival footage or creating stylised content that moves between colour and black-and-white treatments, AI colorization is a practical tool for restoration, creative reinterpretation, or narrative experimentation. It allows historical material to feel more immediate and relatable to modern audiences while preserving the original composition and motion of the source.