Episode 4, Exercise 1 Histogram and QC

[sommerc]

Brief description

1. Introduce the concept of histograms as measuring empirical distributions, i.e. how often does a varible have a certain value. Use repeated dice rolling as an example:

   • start with 10 manually set dice roll results and use matplotlib to compute and plot the histogram.
   • use generated dice rolls (from np.random) to show that histograms visualize the quality of the dice

2. Extend the concept of from dice rolls to pixel intensity values.

   • Plot histogram of one 2D uint8 image with 256 bins (as before with the dice rolls)
   • Introduce the concept of binning in histograms.
   • What are good bin sizes? I. e. histogram is neither too sparse nor too congested

3. Explore image histograms

   • Display various example images with their histogram next to it.
   • Observe and discuss different properties and how they relate to the image (quality), e.g. modes, dim-signal, saturation, sparcity, etc

Learning objective(s)

• In 1. to 2. the Learners use and explore arguments of the plt.hist function. Learning Objective (perhps also np.histogram)
• In 3. the second learning objective (what does a histogram tell us about an image and its quality) is adressed

Volunteer(s)

@sommerc