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This paper investigates the relationship between colorization and pseudo-colorization techniques for converting grayscale images to color. Colorization strives to create visually believable color versions of monochrome images, either replicating the original colors or generating realistic, alternative color schemes. In contrast, pseudo-colorization maps grayscale intensities to pre-defined color palettes to improve visual appeal, enhance content understanding, or aid visual analysis. While colorization is an ill-posed problem with infinitely many RGB solutions, pseudo-colorization relies on mapping functions to deterministically assign colors. This work bridges these techniques by exploring the two following operations: first - deriving pseudo-color from colorized images - this allows for creating stylized or abstract representations from existing colorizations, and second - enriching color diversity in pseudo-colored images - this enhances visual appeal and attractiveness of pseudo-colored images. The paper emphasizes the centrality of decolorization (rgb-to-gray) models in both processes. It focuses on the theoretical underpinnings of these problems but complements them with illustrative examples for clarity.
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