---
title: "Comment by Ahmet Özel on \"How AI Photo Colorization Works: From Grayscale to Natural Color\" | Hashnode"
description: "The claim that colorize-only preserves luminance is worth checking on the exported image, rather than only where the original L channel is recombined with predi"
url: "https://hashnode.com/posts/how-ai-photo-colorization-works-from-grayscale-to-natural-color/6aeea76ab26a750742fa7b48/comment/6aefed8f011114f4c071394f"
---

[Discussion](https://hashnode.com/posts/how-ai-photo-colorization-works-from-grayscale-to-natural-color/6aeea76ab26a750742fa7b48)

Comment [How AI Photo Colorization Works: From Grayscale to Natural Color](https://hashnode.com/posts/how-ai-photo-colorization-works-from-grayscale-to-natural-color/6aeea76ab26a750742fa7b48)

[Ahmet Özel](https://hashnode.com/@ahmetozel)

[4d ago](https://hashnode.com/posts/how-ai-photo-colorization-works-from-grayscale-to-natural-color/6aeea76ab26a750742fa7b48/comment/6aefed8f011114f4c071394f)

The claim that colorize-only preserves luminance is worth checking on the exported image, rather than only where the original L channel is recombined with predicted ab. The later color-space conversion and file export are still part of the product path, and extreme predicted colors are useful test cases for that boundary.

I would compare the recovered lightness of the final output with the input, alongside the face and edge inspection you suggest. Separately measuring structural preservation and color plausibility would make the distinction between colorize-only and restoration testable, instead of relying solely on which model family the interface says it uses.