A better Greyscale algorithm

I'm trying to create a spectral image with a constant grey-scale value for every row. I've written some fantastically slow code that basically tries 1000 different variation between black and white for a given hue and it finds the one whose grey-scale value most closely approximates the target value, resulting in the following image:

On my laptop screen (HP) there is a very noticeable 'dip' near the blue peak, where blue pixels near the bottom of the image appear much brighter than the neighbouring purple and cyan pixels. On my second screen (Acer, which has far superior colour display) the dip is smaller, but still there.

I use the following function to compute the grey-scale approximation of a colour:

Math.Abs开发者_如何学C(targetGrey - (0.2989 * R + 0.5870 * G + 0.1140 * B))

when I convert the image to grey-scale using Paint.NET, I get a perfect black to white gradient, so that part of the code at least works.

So, question: Is this purely an artefact of the display qualities of my screens? Or can the above mentioned grey-scale algorithm be improved upon to give a visually more consistent result?

EDIT: The problem seems to be mostly monitor calibration. Not, I repeat not, a problem with the code.

I'm wondering if its more to do with the way our eyes interpret the colors, rather than screen artifacts.

That said... I am using a very-high quality screen (Dell Ultrasharp, IPS) that has incredible color reproduction and I'm not sure what you mean by "dip" in the blue peak. So either I'm just not noticing it, or my screen doesn't show the same picture and it more color-accurate.

The output looks correct given the greyscale conversion you have used (which I believe is the standard one for sRGB colour spaces).

However - there are lots of tradeoffs in colour models and one of these is that you can get results which aren't visually quite what you want. In your case, the fact that there is a very low blue weight means that a greater amount of blue is needed to get any given greyscale value, hence the blue seems to start lower, at least in terms of how the human eye perceives it.

If your objective is to get a visually appealing spectral image, then I'd suggest altering your function to make the R,G,B weights more equal, and see if you like what you get.