Just a short explanation how I came to this question. I have a ruby module which is basically a hash that gives me HTML "colours", like "slateblue", and gives me back an Array that holds the R,G,B values, like [106, 90, 205] for slateblue.
I googled how to make these R,G,B values into a lighter colour (for mouse cursor on hover effect), and several people told other people when they had a similar problem to just increase the R,G,B values. My current solution, which is a hack, is to add to the R,G,B values, like +20 (capped at 255), and then convert this into a hexstring #FF0000 something.
This seems to work okish but here is the thing now - I have absolutely no understanding about why this works.
Is it so that the 0 always denotes the lowest value of R/G/B and 255 the highest? If so, why is it capped at 255 and not at, don't know, 1024 or some other arbitrary number?
Using 8-bits per color channel - one each for red, green, and blue - yields a large number of colors (2^24 or 16777216), and is sufficient to be used in most applications. Note that there are other color formats with higher precision though.
0 is used for black, while 255 (the maximum stored in 8-bits) denotes "full-on" color.
Adding a specific number to each channel moves the entire color toward (255, 255, 255), or White. If you would like to be more exact in your lightening of the color, you might try converting your RGB color to HSL, doing your addition to the light component only, then converting back to RGB.
You can start research of HSL here: http://en.wikipedia.org/wiki/HSL_and_HSV
Related
I need to make a simple color picker. I have a slider that returns a floating point number between 0 and 1, which I'd like to convert into a color in the manner that you typically see in a color line or color spectrum (red on the left, violet on the right, green and yellow somewhere in the middle).
It seems like there must be some algorithm for converting the liner value into RGB values, but I can't find one. I've tried a few things on my own that did not really work.
I don't need anything super accurate or comprehensive, just something where the user can dial in an approximate color by sliding the slider left and right.
So I know basically nothing about colors apart from the very basics.
I have a color I'm trying to mimic.
I copied it, stuck it in paint, and used the color feature to get the RGB HSL numbers. Great!
RGB: 0; 49; 70
HSL: 132; 240; 33
The issue: When I try to manually input them into Excel, it "autocorrects" the RGB values after I enter in the HSL, and it "autocorrects" the HSL when I re-enter the RGB.
Why is this happening? Is this just an aspect to colors I know nothing about? Some limitation on Excel?
For reference, when I put in just the RGB, I'm much closer (but not quite there) on the color I'm looking for
HSL and RGB are two ways of "translating colors" into numbers.
HSL means Hue, Saturation, Lightness.
Hue is a degree on the color wheel from 0 to 360. 0 is red, 120 is green, 240 is blue.
Saturation is a percentage value; 0% means a shade of gray and 100% is the full color.
Lightness is also a percentage; 0% is black, 100% is white.
RGB means Red, Green, Blue, each of which is given a value between 0 and 255 in Excel.
Check this tool - https://www.w3schools.com/colors/colors_hsl.asp
If you put 0, 49, 70 for HSL you would see that it gets translated to 216, 141, 141 into RGB.
Excel is following the same logic, thus once you adjust the RGB the HSL gets automatically adjusted to represent the same color.
Excel colors are confusing because they don't follow the standard
Although the first reason you may have been confused was if you didn't know that RGB and HSL are two different ways of describing colors (and that every RGB color code has an equivalent HSL color code—see examples below), a second reason many people can get confused when selecting colors in Excel particularly is:
“Frustratingly, Excel does not handle HSL in the standard way. Instead, Excel measures all the numbers where 0 is the lowest and 255 is the biggest. But, it’s a quirk we can handle.” - https://exceloffthegrid.com/convert-color-codes/
“This approach assumes that each of your HSL values can be express in the range of 0 to 255. If, however, your HSL values are either an angle (for hue) or a percentage (for saturation and luminance), then you'll need to convert them manually before entering them in step 6. You can convert an angle value by multiplying the angle by 255 and then dividing by 360. Percentages can be converted by multiplying them by 2.55.” - https://excelribbon.tips.net/T013535_Converting_HSL_to_RGB.html
“To change the lightness (adding white) or darkness (adding black), drag your selection up and down the luminance scale on the right. Notice that the Lum value increases as the color gets lighter. Full luminance is 255 (white), and setting Lum to 0 results in black regardless of the hue and saturation settings.” - https://support.microsoft.com/en-us/office/choosing-colors-in-the-colors-dialog-box-c3d59ddf-65a7-4e62-aad7-f7b8d7684a2d
Examples of converting RGB color codes to HSL
rgb(0, 49, 70) = hsl(198, 100%, 14%)
These independent sites agree with Google that that RGB code converts to that HSL code:
https://colorpicker.me/#003146
https://hslpicker.com/#003146
So if someone told you that rgb(0, 49, 70) was equivalent to hsl(132, 240, 33), they were mistaken (even when using Excel's non-standard way of calculating HSL).
I have two color values in HSI (Hue Saturation and Intensity) and I want a number which represents the visual difference between the two colors. Hue is a number between 0 and 360 inclusive. Saturation is 0 to 1 and Intensity is 0 to 1.
Lets consider for example Red and Blue at Saturation of 100% and Intensity of 100%.
At this website is a way to display the color by entering in the following text.
red is:
hsv 0, 100%, 100%
blue is:
hsv 240, 100%, 100%
Clearly these are two very different colors, and so a simple way I could try to calculate the difference between colors is to use the Hue component and calculate the absolute difference in hue which would be 120 (360-240) since 360 is also equal to 0 in hue.
The problem arises where the Saturation or Intensity is very dark or light, consider a very dark red and blue.
dark red is:
hsv 0, 100%, 20%
dark blue is:
hsv 240, 100% 20%
Obviously the visual difference between these two colors is less than the bright red and blue colors, as a human would state if asked to compare the differences. What I mean here is, ask a friend "Which pair of colors is most different?" they will likely say the top bright red blue.
I am trying to calculate the difference between two colors as a human would notice. If a human being looked at two colors a and b, then two colors c and d, he could notice which ones are the most different. Firstly if the colors are bright (but not too bright) then the difference is hue based. If the colors are too bright such as white or too dark such as black or too grey then the differences are smaller.
It should be possible to have a function diff where x=diff(a,b) and y=diff(c,d) yields x and y, and I can use x and y to compare the differences to find the most different color or least different color.
The WCAG2.0 and 1.0 guidelines both make reference to different equations on perception of color difference:
contrast ratio (http: //www.w3.org/TR/2008/REC-WCAG20-20081211/Overview.html#contrast-ratiodef)
brigtness difference and 3. color difference (http://www.w3.org/TR/AERT#color-contrast).
I tried the Delta-e method(http: //colormine.org/delta-e-calculator/) but it is quasimetric so the difference measurement may change depending on the order you pass the two colors. If in your example you expect diff(a,b) to always equal diff(b,a) then this is not what you want(there may be different algorithms under this name that aren't quasimetric but I haven't looked into it past that site).
I think that the color difference metric is the closest to matching my expectations of color difference measurements. For your example it will yield that diff(a,b) > diff(c,d)
You can test it out for yourself using the tool at this website: http://www.dasplankton.de/ContrastA/
The general answer seems to be what David van Driessche said, to use Delta E. I found some Java code here: https://github.com/kennyliou/GAI
This is a answer to the question, may not be the best answer.
I have a graphics format where for each pixel the previous pixel's RGB value is used (for the first pixel on a line black is used), and then red, green or blue can be modified, or, a pixel can be set to any gray value (previous pixel's value isn't used). All this has been implemented (the easy part).
What would be the best way to convert 24 bit images to this format in the highest possible quality?
Any thoughts are appreciated.
I have more then 1 week reading about selective color change of an image. It meand selcting a color from a color picker and then select a part of image in which I want to change the color and apply the changing of color form original color to color of color picker.
E.g. if I select a blue color in color picker and I also select a red part in the image I should be able to change red color to blue color in all the image.
Another example. If I have an image with red apples and oranges and if I select an apple on the image and a blue color in the color picket, then all apples should be changing the color from red to blue.
I have some ideas but of course I need something more concrete on how to do this
Thank you for reading
As a starting point, consider clustering the colors of your image. If you don't know how many clusters you want, then you will need methods to determine whether to merge or not two given clusters. For the moment, let us suppose that we know that number. For example, given the following image at left, I mapped its colors to 3 clusters, which have the mean colors as shown in the middle, and representing each cluster by its mean color gives the figure at right.
With the output at right, now what you need is a method to replace colors. Suppose the user clicks (a single point) somewhere in your image, then you know the positions in the original image that you will need to modify. For the next image, the user (me) clicked on a point that is contained by the "orange" cluster. Then he clicked on some blue hue. From that, you make a mask representing the points in the "orange" cluster and play with that. I considered a simple gaussian filter followed by a flat dilation 3x5. Then you replace the hues in the original image according to the produced mask (after the low pass filtering, the values on it are also considered as a alpha value for compositing the images).
Not perfect at all, but you could have a better clustering than me and also a much-less-primitive color replacement method. I intentionally skipped the details about clustering method, color space, and others, because I used only basic k-means on RGB without any pre-processing of the input. So you can consider the results above as a baseline for anything else you can do.
Given the image, a selected color, and a target new color - you can't do much that isn't ugly. You also need a range, some amount of variation in color, so you can say one pixel's color is "close enough" while another is clearly "different".
First step of processing: You create a mask image, which is grayscale and varying from 0.0 to 1.0 (or from zero to some maximum value we'll treat as 1.0), and the same size as the input image. For each input pixel, test if its color is sufficiently near the selected color. If it's "the same" or "close enough" put 1.0 in the mask. If it's different, put 0.0. If is sorta borderline, put an in-between value. Exactly how to do this depends on the details of the image.
This might work best in LAB space, and testing for sameness according to the angle of the A,B coordinates relative to their origin.
Once you have the mask, put it aside. Now color-transform the whole image. This might be best done in HSV space. Don't touch the V channel. Add a constant to S, modulo 360deg (or mod 256, if S is stored as bytes) and multiply S by a constant chosen so that the coordinates in HSV corresponding to the selected color is moved to the HSV coordinates for the target color. Convert the transformed S and H, with the unchanged L, back to RGB.
Finally, use the mask to blend the original image with the color-transformed one. Apply this to each channel - red, green, blue:
output = (1-mask)*original + mask*transformed
If you're doing it all in byte arrays, 0 is 0.0 and 255 is 1.0, and be careful of overflow and signed/unsigned problems.