On the right is a photo of British explorers taken with orthocromatic film. Note the red on the flag is much darker than the blue area because the film isn’t receptive of red light. Looking at the spectral sensitivity (here) and (here) it’s clear the violet/blue area is the predominant band with it extending to green/yellow as well.
I took an image from Google, something with the British flag, and made different Channel Maps for it. The greyscaled versions are the output images.
I used the QSE tool on WavelengthPro to make a 400nm image (the violet/blue peak) and a 580nm (the green/yellow peak) and made a 2to3 map of the peaks, the colour response worked well but the data-loss from interpolation was too much. Using the original [R,G,B] channes means I won’t lose any detail, so I tried using mainly those and came up with two maps that were pretty good – GBB and GBBV. Below are those maps and the RGB map for comparison.
This is the RGB (panchromatic) version, the red cross on the flag is lighter than the blue parts and the sky is dark.
This is a GBBtoRGB version, the cross appears darker. It’s not really true to the actual spectral response of the film.
This is a very simple function of WavelengthPro, using the luminance of one image and the hue/saturation of another. All it does is convert from RGB-space to HSL-space then use the L value (lightness) of a different image. In the table below I use a visible light image and an ultraviolet image (I got them from here) and map them in two ways. The first is not a Luminance map, but a GBU map the next is a luminance map which keeps the colours of the visible light and shows them at the lightness of the ultraviolet image.
Visible image: can’t see the graffiti well.
Ultraviolet image: shows up the graffiti well.
GBU map: quite a nice colour palette and shows the graffiti quite well.
Luminance map: has a “Human hue” whilst showing up the graffiti really well.
It is great for showing the ultraviolet characteristics of light whilst keeping the ‘true-colour’ feel that we’ve evolved to love. This idea isn’t new though, nightvision sometimes incorporates visible and thermal bands fused together and computer vision sometimes needs more than visible colour data to interpret a scene. One (less scientific) use is to make thermal imaging look a bit more lovely. Below is a visible image, thermal image and the Luminance map (I got them from here):
Ok this really is an idea that’s fresh in my head, i couldn’t sleep and this
started swimming around..
Multi-Spectrum Imaging: Quantitively assigning the entire EM
spectrum to a corrasponding RGB value and building some sort of multifunctioning
camera that can capture all the different types of shots then transform them
into this image.
An added thought was to assign shades of gray to the entire
sonic spectrum then apply this ‘shader’ to the same image..
Purely experimental, but if it could be done would demonstrate ways of
visualising multiple areas of electromagnetism at the same time.