Monthly Archives: April 2015

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.


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?

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We’re gonna need a montage!

While lots of image analysis and processing is about getting quantifiable numbers out of imaging data, inevitably, there comes a point when you just need to show off some pretty pictures in a presentation, poster or blog (who knew?).

Who would have thought autofluorescence would be so pretty?

Who would have thought autofluorescence would be so pretty?

In this post we’ll be looking at a couple of ways to display your oh-so pretty multichannel pictures.

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Know thy Image Part 2: Image Histograms

In the last post, we looked at the following image to decide if an intensity of 2000 at the tip of the arrowhead was bright or dim. Without knowing the bit depth of the image it’s impossible to tell.

Bright or not bright?

We posed that if this was a 12bit image, that’s fairly bright (2000/4096) but if it’s a 16bit image, then it’s very dim (2000/65536). But why would these two conditions look the same? The answer lies in the histograms and transfer functions…

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