ImageJ with ImagePlot

ImagePlot is a free macro for the open source program ImageJ. It allows for the analysis and visualization of images by hue, brightness, and saturation.

I followed the provided documentation. Below are the steps I took (paraphrased a bit from the documentation).

Prep:

1. Download and unzip ImagePlot_v1.1.zip
2. Open the ImageJ64 app (in the ‘ImageJ’ folder)
3. Set the amount of memory ImageJ can use
   • Edit > Options > Memory & Threads…
   • calculate 70% of your RAM size and type that in Maximum memory in MB (I put 11000MB because I have 16GB of RAM in my Mac Book Pro)
   • quit and restart ImageJ64 in order for the new setting to be saved

Analyze Images:

1. File > Open… ImageMeasure.txt (in the ‘extras’ folder)
2. Macros > Run Macro
3. “Choose images folder to be measured”
4. “Choose folder to save output file measurements.txt”

Create the Visualization:

1. (close the log, results, and ImageMeasure macro)
2. File > Open… ImagePlot.txt
3. Macros > Run Macro
4. match the following settings and press “OK”:
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5. select the measurements.txt file you just created when asked to select the tab-delimited DATA FILE
6. select the folder containing the images you just analyzed
   • Photoshop creates better quality thumbnails MUCH faster than ImageJ. I took the advice of the ImagePlot manual and used Photoshop’s image processor (File > Scripts > Image Processor) to resize all of the images before creating the visualization. I used JPEG quality 10 and resized the photo to 100×100. If you are using Instagram photos, you’ll need to change your Photoshop Preferences or many of them will not open. So, go to Photoshop > Preferences > File Handling:
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7. choose the data columns to use for rendering visualization:
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8. Options: put a check next to “Canvas” and “Images” then press “OK”
9. Canvas options (width and height):
   • Unfortunately, ImageJ has a file rendering size of 2.5GB, so there is a bit of math to execute in order to choose your canvas size.
   • The documentation explains that in order to calculate the maximum possible dimensions one should use the following formula:
     • Visualization size = width (in pixels) x Height (in pixels) x pixel size in memory (1 byte for 8-bit greyscale or 4 bytes for 24-bit color images)
   • So, desiring 24-bit color images:
     • 2,500,000,000 bytes (2.5GB) divided by 4 bytes = 625,000,000
     • using this site, I plugged 625000000 in the number of pixels and used the ratio of our 4k display (1.78) to determine I needed to make my canvas 33354 x 18738
10. Canvas options (border size):
    • As noted here in the documentation, you need to make the border size large enough to hold the height of an entire image. On the next screen, you get to choose the width of the image thumbnails … so choose your border accordingly now.
11. Images options:
    • I left the thumbnail width with the 100px default (this is what I resized them to using Photoshop).
    • I also checked the “Smooth Resize” option which REALLY slowed down the process, but technically should have rendered better quality image thumbnails.
12. now you wait and watch it render …
13. File > Save as …