When I convert black (rgb(0,0,0)) to LAB and back again it comes out as 19, 0, 10.
Is there a modified formula that expands the Lab color-space for 1:1 conversion? And if not, are there any other color-spaces that maintain the property of "the same amount of numerical change in these values corresponds to roughly the same amount of visually perceived change"?
I want to run k-means clustering on some images and it works better in Lab space.
The short answer is the code library you are using has bugs.
And it does not seem to be actively maintained.
FWIW, when you are looking at values, remember that:
#000
sRGB 0,0,0 = linearRGB 0.0,0.0,0.0 = XYZ 0,0,0 = Lab 0,0,0
(All spaces 0,0,0)
#FFF
sRGB 255,255,255 = linearRGB 1.0,1.0,1.0 = XYZ 0.9505,1.0,1.0888 = Lab 100,0,0
(sRGB is D65, this assumes D65 2° observer)
#777
sRGB 119,119,119 = linearRGB 0.1845,0.1845,0.1845 = XYZ 0.1753,0.1845,0.2009 = Lab 50.03,0,0
(using BruceLindbloom Matrix)
Pseudocode
More correct code can be found here:
https://www.easyrgb.com/en/math.php
However, this code is NOT javascript — the code on this site is pseudocode, and so it needs to be modified (i.e. you need to use Math.pow and not ^ )
Python
There is a good Python based library here, and it is actively maintained:
https://github.com/colour-science/colour
MATH
The actual math and discussion can be found on Bruce Lindbloom's site:
http://www.brucelindbloom.com/index.html?Math.html
He also has some color calculators that are JS that might be helpful to you.
Happy to answer other questions, lemme know...