Dichromacy, or How Dogs View the World

The original source code for this post is wrong as pointed out by a friendly soul in the comments section. I have since updated the images on this post to reflect that fact /ssodelta

This post was updated July 1st, 2016. The new source is based on the DELTA Colour Library. The full code for the protanopia-filter is:

public class ProtanopiaFilter implements DImageFilter {

 @Override
 public Colour filter(int x, int y, Colour[][] raster) {
 Colour c = raster[x][y];
 c.convert(ColourSpace.LMS);
 
 double[] lms = c.getData();
 
 double Lp = 2.02344*lms[1] - 2.52581*lms[2],
 Mp = lms[1],
 Sp = lms[2];
 
 return new Colour(new double[]{Lp, Mp, Sp}, ColourSpace.LMS);
 }

}

Most humans see a whole bunch of colors – red, green, blue, violet, maroon etc., but some people are unfortunately born color-blind, and thus have trouble differentiating hues, which regular people find easy. For example, the red-green color blindness, which I’ll assume most people have heard of. Basically, if you’re red-green color blind, this image looks uniform:

This is because the human eye interprets color using three color receptors – red, green and blue. However, in some people, one or more of these receptors don’t work as well, making it harder to tell certain colors apart. When you only have two color receptors, you have a condition called dichromacy. Some animals, however, are permanent dichromats – this includes our canine friends – dogs are dichromats. There are several kinds of dichromacy, protanopia is the most common amongst humans, and there is a general consensus that this is how dogs view the world. Consider this rainbow:

If you have protanopia (or is a dog) this rainbow would look something like this instead

Notice how similar the blue and green colors look to a dog – no wonder it can’t as easily as us spot a blue ball in green grass. Anyway, the above protanopia rainbow was rendered using a program I wrote myself. I’ll account for how to convert regular RGB color codes to their protanopia representation in the following section.

To be able to perform this conversion, we first need to convert RGB color space into LMS color space. LMS color space is another way to represent colors using their approximate wavelengths. Remember how the human eye has three receptors? Each color channel in LMS represents one of these receptors:

Human color vision and the LMS color space.

To do this, we use the following equation: (reference)

This is just simple matrix multiplication, and we now have another triplet LMS representing our pixel. Next up, we’ll convert this to protanopia vision using the following formula; all represent the protanopia version of the channel:

Notice how the M and S channels remain the same. If we discuss other types of color blindness, they might also change. Finally, we’ll convert back from LMS to RGB using the following formula:

I have made two classes in Java, that do this exact conversion, which I have included in the link at the top of this post – and a wrapper class for BufferedImage, which eases the conversion. Using this formula, we can imagine how dogs view different scenarios:

A colorful meadow (credit):

Beautiful tropical birds (credit):

Personally, I’m glad I have full color vision, as the world is much more beautiful when you have a wide range of colors, however sometimes I’m bummed out by the fact that I’m not a mantis shrimp – they have 16 color receptors, completely dwarfing our 3 color receptors. I don’t have the brain power to even understand 4 color receptors, so 16 seems completely mind-boggling to me.