This document discusses image compression and quality. It explores how lossy and lossless compression algorithms can affect image quality and file size. The document outlines an experimental procedure to test different compression settings on various image types. Participants are instructed to compress images using low, medium, and high quality settings for different algorithms. The compressed images will then be printed, labeled anonymously, and rated for quality. Comparing the ratings to the compression levels will allow analysis of the tradeoffs between file size and image quality using different algorithms and settings. The goal is to determine the amount of compression an image can withstand before quality noticeably decreases and if some image types are less tolerant of compression than others.

1. Image Compression vs. Image Quality
Finding the Best Tradeoff

2. twe different image compression
algprithms and rate them for:
•Image quality
subjective quality rannking
resolution
come uo with your own quality measure
•Compression ratio

3. In order to make the most efficient
use of images
It is improtant to match the spatial
and color resolution of the image to
the spatial and color resorution of
the intended output device.

4. Pixel An image with 24 bits of color
information for each pixel will
generally look better than an
image with only 16 bits of color
information for each pixel.
Agein, the better the color
resolution, the bigger the image file.

5. Algorithmes of Compression
Image compression algorithms are designed to
minimize image file size in order to speed up
image data transmission.

6. Question 1
How much can an image be compressed
with a "lossy" algorithm before you
start to notice a difference
in image quality?
Do some types of images lose image quality
more quickly than others?

7. Question 2
What are the advantages of lossy image
compression over lossless image
compression?
What are the advantages of lossless image
compression over lossy image compression?

8. Question 3
Does JPEG image compression work equally
well with all types of images?
If not, what types of images compress "better"?
What types of images compress "worse"?

9. Experimental Procedure 1
Read about the different options in your program's
help file.
Select "low", "medium" and "high" image quality
compression settings for each algorithm you are using.
Use your image-writing program to save each image
with the "low", "medium", and "high" image quality
settings you selected for each compression algorithm.

10. Experimental Procedure 2
Name each file so that you can tell which
settings and algorithm were used to create it,
and which original image it came from.
Have your assistant help you to print the images, labeling
them on the back with a coded name. Your assistant
should be able to match the coded names to the original
ones, but you should not know the code. All of the images
should be printed with the same paper type, printer and
printer settings.

11. Experimental Procedure 3
Study the images, and arrange them in order of image
quality from best to worst. Then assign a "quality score" to
the images rank them equally.
After all of the images have been rated, have your assistant
reveal the codes. Now you can add the compression
information to your ratings, and make comparisons.
Compare the trade-offs in file size vs. image quality
for different image types.

12. Materials and Equipment
•computer
•image writing software
•digital image file
•printer, for comparing images
•an assistant to secretly label the print-outs, so
you can rate the images “blind”.

13. Variations 1
Use a resolution target as one of your test images. For
example, here is a US Air Force bar target. The bars are
arranged in groups of six at progressively smaller sizes.
Make a set of images with "low", "medium" and "high"
compression settings. Print the images exactly the same
way Study the image print-outs with a magnifying glass to
see the smallest set of features you can distinguish, and
compare this to the compression ratio.

14. Variations 2
If you print out your images at
"thumbnail" size, is a higher compression ratio more or
less noticeable than when the image is printed at normal
size?
"zip" files: another common file compression method is the
"zip" file, a lossless compression method. Can compressed
image files be further compressed by "zipping" them?

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