Is their any GLSL shader that can help me to "boost" the color of a texture ? How to write such shader ? I would like to do something like the picture below :
It seems they are mostly boosting saturation here, so that's what you'd need to do in your fragment shader.
To boost saturation, you need to take your data from the RVB color space to the HSL (hue saturation lightness) space.
you then need to do:
hslColor = vec3(hslCOlor.x, hslColor.y * **boost**, hslCOlor.z);
Of course to do that you actually need to get into the right color space. This isn't really an openGL issue, I found this website that does the convertion:
https://www.rapidtables.com/convert/color/rgb-to-hsl.html
They also give formulas for the conversion:
R' = R
G' = G
B' = B
Cmax = max(R', G', B')
Cmin = min(R', G', B')
Δ = Cmax - Cmin
L = (Cmax + Cmin) / 2
THat way you can get HSL from RVB. Once you've done your saturation boost, you need to take your colros back to RVB colorspace
it'ssa good news that the same website seem to offer the same capabilities!
https://www.rapidtables.com/convert/color/hsl-to-rgb.html
When 0 ≤ H < 360, 0 ≤ S ≤ 1 and 0 ≤ L ≤ 1:
C = (1 - |2L - 1|) × S
X = C × (1 - |(H / 60°) mod 2 - 1|)
m = L - C/2
(R,G,B) = ((R'+m), (G'+m),(B'+m))
I removed the 255 from their formulas because usually you work on [0,1] in GLSL.
With this you should be able to do all sort of transformations on the colors to manipulate them in a way that is similar to the simple tools of photoshop.
EDIT it should be noted that I mostly talked about boosting saturation, but they might be doing stuffs significantly more complex in your exemple. But working in HSL will still be a good thing to do if you are working with colors to edit photographs.
Related
Currently I use the following formula to gamma correct colors (convert them from RGB to sRGB color space) after the lighting pass:
output = pow(color, vec3(1.0/2.2));
Is this formula the correct formula for gamma correction? I ask because I have encountered a few people saying that its not, and that the correct formula is more complicated and has something to do with power 2.4 rather than 2.2. I also heard something that the three color R, G and B should have different weights (something like 0.2126, 0.7152, 0.0722).
I am also curious which function does OpenGL use when GL_FRAMEBUFFER_SRGB is enabled.
Edit:
This is one of many topics covered in Guy Davidson's talk "Everything you know about color is wrong". The gamma correction function is covered here, but the whole talk is related to color spaces including sRGB and gamma correction.
Gamma correction may have any value, but considering linear RGB / non-linear sRGB conversion, 2.2 is an approximate, so that your formula may be considered both wrong and correct:
https://en.wikipedia.org/wiki/SRGB#Theory_of_the_transformation
Real sRGB transfer function is based on 2.4 gamma coefficient and has discontinuity at dark values like this:
float Convert_sRGB_FromLinear (float theLinearValue) {
return theLinearValue <= 0.0031308f
? theLinearValue * 12.92f
: powf (theLinearValue, 1.0f/2.4f) * 1.055f - 0.055f;
}
float Convert_sRGB_ToLinear (float thesRGBValue) {
return thesRGBValue <= 0.04045f
? thesRGBValue / 12.92f
: powf ((thesRGBValue + 0.055f) / 1.055f, 2.4f);
}
In fact, you may find even more rough approximations in some GLSL code using 2.0 coefficient instead of 2.2 and 2.4, so that to avoid usage of expensive pow() (x*x and sqrt() are used instead). This is to achieve maximum performance (in context of old graphics hardware) and code simplicity, while sacrificing color reproduction. Practically speaking, the sacrifice is not that noticeable, and most games apply additional tone-mapping and user-managed gamma correction coefficient, so that result is not directly correlated to sRGB standard.
GL_FRAMEBUFFER_SRGB and sampling from GL_SRGB8 textures are expected to use more correct formula (in case of texture sampling it is more likely pre-computed lookup table on GPU rather than real formula as there are only 256 values to convert). See, for instance, comments to GL_ARB_framebuffer_sRGB extension:
Given a linear RGB component, cl, convert it to an sRGB component, cs, in the range [0,1], with this pseudo-code:
if (isnan(cl)) {
/* Map IEEE-754 Not-a-number to zero. */
cs = 0.0;
} else if (cl > 1.0) {
cs = 1.0;
} else if (cl < 0.0) {
cs = 0.0;
} else if (cl < 0.0031308) {
cs = 12.92 * cl;
} else {
cs = 1.055 * pow(cl, 0.41666) - 0.055;
}
The NaN behavior in the pseudo-code is recommended but not specified in the actual specification language.
sRGB components are typically stored as unsigned 8-bit fixed-point values.
If cs is computed with the above pseudo-code, cs can be converted to a [0,255] integer with this formula:
csi = floor(255.0 * cs + 0.5)
Here is another article describing sRGB usage in OpenGL applications, which you may find useful: https://unlimited3d.wordpress.com/2020/01/08/srgb-color-space-in-opengl/
I am fond of random generation - and random colors - so I decided to combine them both and made a simple 2d landscape generator. What my idea was is to, depending on how high a block is, (yes, the terrain is made of blocks) make it lighter or darker, where things nearest the top are lighter, and towards the bottom are darker. I got it working in grayscale, but as I figured out, you cannot really use a base RGB color and make it lighter, given that the ratio between RGB values, or anything of the sort, seem to be unusable. Solution? HSL. Or perhaps HSV, to be honest I still don't know the difference. I am referring to H 0-360, S & V/L = 0-100. Although... well, 360 = 0, so that is 360 values, but if you actually have 0-100, that is 101. Is it really 0-359 and 1-100 (or 0-99?), but color selection editors (currently referring to GIMP... MS paint had over 100 saturation) allow you to input such values?
Anyhow, I found a formula for HSL->RGB conversion (here & here. As far as I know, the final formulas are the same, but nonetheless I will provide the code (note that this is from the latter easyrgb.com link):
Hue_2_RGB
float Hue_2_RGB(float v1, float v2, float vH) //Function Hue_2_RGB
{
if ( vH < 0 )
vH += 1;
if ( vH > 1 )
vH -= 1;
if ( ( 6 * vH ) < 1 )
return ( v1 + ( v2 - v1 ) * 6 * vH );
if ( ( 2 * vH ) < 1 )
return ( v2 );
if ( ( 3 * vH ) < 2 )
return ( v1 + ( v2 - v1 ) * ( ( 2 / 3 ) - vH ) * 6 );
return ( v1 );
}
and the other piece of code:
float var_1 = 0, var_2 = 0;
if (saturation == 0) //HSL from 0 to 1
{
red = luminosity * 255; //RGB results from 0 to 255
green = luminosity * 255;
blue = luminosity * 255;
}
else
{
if ( luminosity < 0.5 )
var_2 = luminosity * (1 + saturation);
else
var_2 = (luminosity + saturation) - (saturation * luminosity);
var_1 = 2 * luminosity - var_2;
red = 255 * Hue_2_RGB(var_1, var_2, hue + ( 1 / 3 ) );
green = 255 * Hue_2_RGB( var_1, var_2, hue );
blue = 255 * Hue_2_RGB( var_1, var_2, hue - ( 1 / 3 ) );
}
Sorry, not sure of a good way to fix the whitespace on those.
I replaced H, S, L values with my own names, hue, saturation, and luminosity. I looked it back over, but unless I am missing something I replaced it correctly. The hue_2_RGB function, though, is completely unedited, besides the parts needed for C++. (e.g. variable type). I also used to have ints for everything - R, G, B, H, S, L - then it occured to me... HSL was a floating point for the formula - or at least, it would seem it should be. So I made variable used (var_1, var_2, all the v's, R, G, B, hue, saturation, luminosity) to floats. So I don't beleive it is some sort of data loss error here. Additionally, before entering the formula, I have hue /= 360, saturation /= 100, and luminosity /= 100. Note that before that point, I have hue = 59, saturation = 100, and luminosity = 70. I believe I got the hue right as 360 to ensure 0-1, but trying /= 100 didn't fix it either.
and so, my question is, why is the formula not working? Thanks if you can help.
EDIT: if the question is not clear, please comment on it.
Your premise is wrong. You can just scale the RGB color. The Color class in Java for example includes commands called .darker() and .brighter(), these use a factor of .7 but you can use anything you want.
public Color darker() {
return new Color(Math.max((int)(getRed() *FACTOR), 0),
Math.max((int)(getGreen()*FACTOR), 0),
Math.max((int)(getBlue() *FACTOR), 0),
getAlpha());
}
public Color brighter() {
int r = getRed();
int g = getGreen();
int b = getBlue();
int alpha = getAlpha();
/* From 2D group:
* 1. black.brighter() should return grey
* 2. applying brighter to blue will always return blue, brighter
* 3. non pure color (non zero rgb) will eventually return white
*/
int i = (int)(1.0/(1.0-FACTOR));
if ( r == 0 && g == 0 && b == 0) {
return new Color(i, i, i, alpha);
}
if ( r > 0 && r < i ) r = i;
if ( g > 0 && g < i ) g = i;
if ( b > 0 && b < i ) b = i;
return new Color(Math.min((int)(r/FACTOR), 255),
Math.min((int)(g/FACTOR), 255),
Math.min((int)(b/FACTOR), 255),
alpha);
}
In short, multiply all three colors by the same static factor and you will have the same ratio of colors. It's a lossy operation and you need to be sure to crimp the colors to stay in range (which is more lossy than the rounding error).
Frankly any conversion to RGB to HSV is just math, and changing the HSV V factor is just math and changing it back is more math. You don't need any of that. You can just do the math. Which is going to be make the max component color greater without messing up the ratio between the colors.
--
If the question is more specific and you simply want better results. There are better ways to calculate this. You rather than static scaling the lightness (L does not refer to luminosity) you can convert to a luma component. Which is basically weighted in a specific way. Color science and computing is dealing with human observers and they are more important than the actual math. To account for some of these human quirks there's a need to "fix things" to be more similar to what the average human perceives. Luma scales as follows:
Y = 0.2126 R + 0.7152 G + 0.0722 B
This similarly is reflected in the weights 30,59,11 which are wrongly thought to be good color distance weights. These weighs are the color's contribution to the human perception of brightness. For example the brightest blue is seen by humans to be pretty dark. Whereas yellow (exactly opposed to blue) is seen to be so damned bright that you can't even make it out against a white background. A number of colorspaces Y'CbCr included account for these differences in perception of lightness by scaling. Then you can change that value and it will be scaled again when you scale it back.
Resulting in a different color, which should be more akin to what humans would say is a "lighter" version of the same color. There are better and better approximations of this human system and so using better and fancier math to account for it will typically give you better and better results.
For a good overview that touches on these issues.
http://www.compuphase.com/cmetric.htm
I'm porting a MATLAB piece of code in C/C++ and I need to map many RGB colors in a graph to an integer interval.
Let [-1;1] be the interval a function can have a value in, I need to map -1 and any number below it to a color, +1 and any number above it to another color, any number between -1 and +1 to another color intermediate between the boundaries. Obviously numbers are infinite so I'm not getting worried about how many colors I'm going to map, but it would be great if I could map at least 40-50 colors in it.
I thought of subdividing the [-1;1] interval into X sub-intervals and map every one of them to a RGB color, but this sounds like a terribly boring and long job.
Is there any other way to achieve this? And if there isn't, how should I do this in C/C++?
If performance isn't an issue, then I would do something similar to what High Performance Mark suggested, except maybe do it in HSV color space: Peg the S and V values at maximum and vary the H value linearly over a particular range:
s = 1.0; v = 1.0;
if(x <= -1){h = h_min;}
else if(x >= 1){h = h_max;}
else {h = h_min + (h_max - h_min)*0.5*(x + 1.0);}
// then convert h, s, v back to r, g, b - see the wikipedia link
If performance is an issue (e.g., you're trying to process video in real-time or something), then calculate the rgb values ahead of time and load them from a file as an array. Then simply map the value of x to an index:
int r, g, b;
int R[NUM_COLORS];
int G[NUM_COLORS];
int B[NUM_COLORS];
// load R, G, B from a file, or define them in a header file, etc
unsigned int i = 0.5*(x + 1.0);
i = MIN(NUM_COLORS-1, i);
r = R[i]; g = G[i]; b = B[i];
Here's a poor solution. Define a function which takes an input, x, which is a float (or double) and returns a triplet of integers each in the range 0-255. This triplet is, of course, a specification of an RGB color.
The function has 3 pieces;
if x<=-1 f[x] = {0,0,0}
if x>= 1 f[x] = {255,255,255}
if -1<x<1 f[x] = {floor(((x + 1)/2)*255),floor(((x + 1)/2)*255),floor(((x + 1)/2)*255)}
I'm not very good at writing C++ so I'll leave this as pseudocode, you shouldn't have too much problem turning it into valid code.
The reason it isn't a terribly good function is that there isn't a natural color gradient between the values that this plots through RGB color space. I mean, this is likely to produce a sequence of colors which is at odds to most people's expectations of how colors should change. If you are one of those people, I invite you to modify the function as you see fit.
For all of this I blame RGB color space, it is ill-suited to this sort of easy computation of 'neighbouring' colors.
I have a given color and want to create variations of it in terms of hue, saturation and lightness.
I found a webpage which creates variations the way I would like it (See http://coloreminder.com/). However, I do not entirely understand how these variations are created for an arbitrary color. From what I can tell from considering created variations at this home page, it seems not to be enough to simply change the HSL values separately to create variations.
Hence, I wanted to ask if anybody knows an approach for creating these variations, or ideally knows where to get a piece of code to adopt this kind of color variations creation in my own program?
I am using C++ and QT.
EDIT: Thank you for your replies! Actually the variations of the given homepage really only varies the HSL values separately in 10% steps. I got confused since I compared the values with HSV values in color picker of my program.
From what I can tell from considering created variations at this home page, it seems not to be enough to simply change the HSL values seperately to create variations.
Really? The interface seems to be clear enough about what modifications it makes. You can select "hue", "saturation" or "luminance" and it shows 9 variations on that channel. The following MATLAB script will plot the different variations in a similar way (although in the HSV color space, not HSL).
% display n variations of HTML-style color code.
function [] = colorwheel ( hex, n )
% parse color code.
rgb = hex2rgb(hex);
% render all variations.
h = figure();
for j = 1 : 3,
% build n variations on current channel.
colors = variantsof(rgb, j, n);
% display variations.
for i = 1 : n,
% generate patch of specified color.
I = zeros(128, 128, 3);
I(:,:,1) = colors(i, 1);
I(:,:,2) = colors(i, 2);
I(:,:,3) = colors(i, 3);
% render patches side-by-side to show progression.
imshow(I, 'parent', ...
subplot(3, n, (j-1)*n+i, 'parent', h));
end
end
end
% parse HTML-style color code.
function [ rgb ] = hex2rgb ( hex )
r = double(hex2dec(hex(1:2))) / 255;
g = double(hex2dec(hex(3:4))) / 255;
b = double(hex2dec(hex(5:6))) / 255;
rgb = [r g b];
end
% generate n variants of color on j-th channel.
function [ colors ] = variantsof ( rgb, j, n )
colors = zeros(n, 3);
for i = 1 : n,
% convert to HSV.
color = rgb2hsv(rgb);
% apply variation to selected channel.
color(j) = color(j) + ((i-1) / n);
if color(j) > 1.0,
color(j) = color(j) - 1.0;
end
% convert to RGB.
colors(i,:) = hsv2rgb(color);
end
% order colors with respect to channel.
if j > 1,
colors = sortrows(colors, j);
end
end
Using the "goldenrod" sample color, as:
colorwheel('daa520', 9);
I get:
The first row is a variation on hue, the second on saturation and the third on value. The outputs don't correspond exactly to the ones on the coloreminder.com, but this is explained by the difference in color space and exact value used in permutations.
Have you read through the documentation for QColor?
The QColor class itself provides plenty of useful functions for manipulating colors in pretty much any way you can think of, and the documentation itself explains some basic color theory as well.
I was told to use distance formula to find if the color matches the other one so I have,
struct RGB_SPACE
{
float R, G, B;
};
RGB_SPACE p = (255, 164, 32); //pre-defined
RGB_SPACE u = (192, 35, 111); //user defined
long distance = static_cast<long>(pow(u.R - p.R, 2) + pow(u.G - p.G, 2) + pow(u.B - p.B, 2));
this gives just a distance, but how would i know if the color matches the user-defined by at least 25%?
I'm not just sure but I have an idea to check each color value to see if the difference is 25%. for example.
float R = u.R/p.R * 100;
float G = u.G/p.G * 100;
float B = u.B/p.B * 100;
if (R <= 25 && G <= 25 && B <= 25)
{
//color matches with pre-defined color.
}
I would suggest not to check in RGB space. If you have (0,0,0) and (100,0,0) they are similar according to cababungas formula (as well as according to casablanca's which considers too many colors similar). However, they LOOK pretty different.
The HSL and HSV color models are based on human interpretation of colors and you can then easily specify a distance for hue, saturation and brightness independently of each other (depending on what "similar" means in your case).
"Matches by at least 25%" is not a well-defined problem. Matches by at least 25% of what, and according to what metric? There's tons of possible choices. If you compare RGB colors, the obvious ones are distance metrics derived from vector norms. The three most important ones are:
1-norm or "Manhattan distance": distance = abs(r1-r2) + abs(g1-g2) + abs(b1-b2)
2-norm or Euclidean distance: distance = sqrt(pow(r1-r2, 2) + pow(g1-g2, 2) + pow(b1-b2, 2)) (you compute the square of this, which is fine - you can avoid the sqrt if you're just checking against a threshold, by squaring the threshold too)
Infinity-norm: distance = max(abs(r1-r2), abs(g1-g2), abs(b1-b2))
There's lots of other possibilities, of course. You can check if they're within some distance of each other: If you want to allow up to 25% difference (over the range of possible RGB values) in one color channel, the thresholds to use for the 3 methods are 3/4*255, sqrt(3)/4*255 and 255/4, respectively. This is a very coarse metric though.
A better way to measure distances between colors is to convert your colors to a perceptually uniform color space like CIELAB and do the comparison there; there's a fairly good Wikipedia article on the subject, too. That might be overkill depending on your intended application, but those are the color spaces where measured distances have the best correlation with distances perceived by the human visual system.
Note that the maximum possible distance is between (255, 255, 255) and (0, 0, 0), which are at a distance of 3 * 255^2. Obviously these two colours match the least (0% match) and they are a distance 100% apart. Then at least a 25% match means a distance less than 75%, i.e. 3 / 4 * 3 * 255^2 = 9 / 4 * 255 * 255. So you could just check if:
distance <= 9 / 4 * 255 * 255