Seeing the world in Black and White

In the last post, I covered a few ways to visually present your data, The astute reader may have noticed that the single channels were always presented in greyscale, while colour was saved for the merged or composite channels.

2015-03-montage_09

This is one of those gripes that make me sound like a broken record, but you can open just about any article with imaging and find an example of it. Why do otherwise sensible people present single-channel data in colour?

Simply put: because it looks nice. If you’re giving a presentation or making a poster, you will probably want something more colourful and eye-catching than greyscale images throughout. I think it’s fair to say however, that doing this in publications makes it much harder to interpret the data.

So why is this such a big deal?

The human eye is a wonderful device but objective, it is not. Your brain judges colour based on its surrounding, attempting to take into account illumination as well reflected light. There are countless examples of these sorts of optical illusions (see some great ones here) and it would be remiss of me not to mention that dress.

The other issue here is one of colour resolution. The human eye has (broadly) two types of receptor cells Cones for colour vision and Rods for monochrome. Cones come in Red, Green and Blue flavours but here’s the thing: the three are not identically sensitive:

By Skatebiker, vector by Adam Rędzikowski (File:Evesensitivity.svg, vectorised) [CC BY-SA 3.0 (http://creativecommons.org/licenses/by-sa/3.0)], via Wikimedia Commons.

By Skatebiker, vector by Adam Rędzikowski (File:Evesensitivity.svg, vectorised) [CC BY-SA 3.0 (http://creativecommons.org/licenses/by-sa/3.0)%5D, via Wikimedia Commons.

The practical result here is that if you look at the same image with three different lookup tables the green will look brighter than either the red or green:

2015-03-colour_01You’ll probably notice, however that the greyscale image looks brighter still, with more detail being immediately visible. Partly this is due to the fact that you have many more Rods than Cones and that they’re more sensitive (which is why low-light vision is typically monochrome). As a point of interest, the absorption maxima for rods is about 498nm, which is also why the green signal above looks brighter than the red or blue.

Best Practice?

As you’ve guessed, I’m a fierce proponent of greyscale for single-channel data. The previous post details how to adjust Lookup tables to get greyscale images and montages. Other than changing your practice, just keep moaning at Lab Meetings, Journal Clubs and Editors!

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One thought on “Seeing the world in Black and White

  1. Pingback: Go Figure, Part 2 | Post-Acquisition

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