In perceptual color models like CIELAB, white is not a fixed point but a context-dependent reference. It varies based on lighting conditions and observer assumptions.

Key insight:
Neutrality is not singular—it exists as a range of near-neutral values.

Instead of direct tracing, you can now feed high-resolution images into generative vectorization models trained on painterly datasets. This method is less about duplication and more about recomposition—a digital echo of your analog trance. Ideally shoot for midway between just the facts and every single fiber.

FOR REFERENCE

(‘Hue’2.4)

Color quantization sounds technical at first…like something hidden inside an image compression algorithm or buried in the rendering pipeline of an old graphics engine. and technically, that is 100% correct. We wanted to develop a creative programming language, however, that begins to treat quantization as something more interesting: a philosophy of limitation or memory device. ‘HueRemindMe’ (‘26) is a coding project aimed at expanding and shaping perception through deliberate reduction.

Reframing the mechanics of digital seeing:

Historically, many quantization systems were developed as engineering solutions. Median-cut quantization, introduced in the early 1980s and still foundational today, divides color space into optimized regions to preserve visual similarity while reducing palette size. This is an interactive module (ver 2.4) in open beta. Feel free to explore to your heart’s content!