Lookup table

Prerequisites

Before starting this lesson, you should be familiar with:

• Basic properties of images and pixels

Learning Objectives

After completing this lesson, learners should be able to:

• Understand how the numerical values in an image are transformed into colourful images.

• Understand what a lookup table (LUT) is and how to adjust it.

• Appreciate that choosing the correct LUT is a very serious responsibility when preparing images for a talk or publication.

Motivation

Images are a collection of a lot (millions) of values, which is information that is hard to process for our human brains. Thus, one typically assigns a color to each distinct value, by means of a lookup table (LUT). There is no fix recipe for how to adjust this mapping from numbers to colors. It is easy to chose a mapping that hides certain information in an image, while emphasising other information. Thus, configuring this mapping properly is a great responsibility that scientists have to take on when presenting their image data.

Concept map

Example figure

Activity

• Open the image xy_8bit__nuclei_high_dynamic_range.tif
• Explore different single color LUTs and LUT settings
• Visualise the LUT, e.g. as an inset in the image as in above figure.
• Appreciate that LUT settings do not change the pixel values
• Appreciate that a single color LUT will not allow you to see all nuclei without clipping
• Appreciate that certain colors like blue are not so good for seeing different intensities (grey values are probably the best).
• Explore multi color LUTs for visualisation of such a “high dynamic range” (big difference of intensities) image.

ImageJ Macro & GUI

// File › Close All
run("Close All");
// File › Open...
open("https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_8bit__nuclei_high_dynamic_range.tif");
// Image › Rename...
rename("gray_0_255"); 
// Analyze › Tools › Calibration Bar...
run("Calibration Bar...", "location=[Upper Left] fill=None label=White number=5 decimal=0 font=5 zoom=0.7 overlay");
// Image › Duplicate...
run("Duplicate...", "title=gray_0_43");
// Image › Adjust › Brightness/Contrast..
setMinAndMax(0, 43);
run("Calibration Bar...", "location=[Upper Left] fill=None label=White number=5 decimal=0 font=5 zoom=0.7 overlay");
run("Duplicate...", "title=blue_0_255");
run("Blue");
setMinAndMax(0, 255);
run("Calibration Bar...", "location=[Upper Left] fill=None label=White number=5 decimal=0 font=5 zoom=0.7 overlay");
run("Duplicate...", "title=fire_0_255");
run("Fire");
run("Calibration Bar...", "location=[Upper Left] fill=None label=White number=5 decimal=0 font=5 zoom=0.7 overlay");
run("Duplicate...", "title=hilo_0_255");
run("HiLo");
run("Calibration Bar...", "location=[Upper Left] fill=None label=White number=5 decimal=0 font=5 zoom=0.7 overlay");
run("Duplicate...", "title=hilo_20_100");
setMinAndMax(20, 100);
run("Calibration Bar...", "location=[Upper Left] fill=None label=White number=5 decimal=0 font=5 zoom=0.7 overlay");
run("Tile");

Exercises

ImageJ Macro & GUI

Open those two image:

• xy_calibrated_16bit__nuclear_protein_control.tif
• xy_calibrated_16bit__nuclear_protein_treated.tif

Display the images with the same gray scale LUT and the same LUT settings (this is what one typically should do for a presentation or publication). To achieve this it is convenient to use the [ Set ] button in [ Image › Adjust › Brightness/Contrast… ] and check “[X] propagate to …”

Visualise the LUT as an inset in both images.

Solution

run("Close All");

// File › Open...
open("https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_calibrated_16bit__nuclear_protein_control.tif");
// [Image › Lookup Tables › Grays ]
run("Grays");
// [ Image › Adjust › Brightness/Contrast... ]
setMinAndMax(8, 3804);
// Analyze › Tools › Calibration Bar...
run("Calibration Bar...", "location=[Upper Left] fill=[Dark Gray] label=White number=5 decimal=0 font=10 zoom=2 overlay");

open("https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_calibrated_16bit__nuclear_protein_treated.tif");
run("Grays");
setMinAndMax(8, 3804);
run("Calibration Bar...", "location=[Upper Left] fill=[Dark Gray] label=White number=5 decimal=0 font=10 zoom=2 overlay");

// Window › Tile
run("Tile");

Assessment

Calculate the brightness:

1. value = 49, min = 10, max = 50, brightness = ?
2. value = 100, min = 0, max = 65, brightness = ?
3. value = 10, min = 20, max = 65, brightness = ?

Solution

1. 0.975
2. 1.538 ( -> 1 )
3. -0.15 ( -> 0 )

Fill in the blanks

Fill in the blanks using those words: larger than, smaller than

1. Pixels with values _____ max will appear saturated.
2. Pixels with values _____ the min will appear black (using a single color LUT).

Solution

1. larger than
2. smaller than

Follow-up material

We recommend reading these modules next:

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