Explain how data can be compressed using run length encoding (RLE).

The idea

Run length encoding replaces repeated consecutive values with a count followed by the value, so long runs of identical data take less space. To encode, scan the data left to right, count how many times each value repeats in a row, and write the count then the value; a run of one is written as 1 followed by the value. For example, the pixel row AAAAA BB CCCCC becomes 5A 2B 5C. To decode, read each count and repeat the following value that many times. RLE works best where data has long runs, such as simple images with large areas of one colour, and poorly where values alternate, because short runs add count characters and can increase size. It is lossless, so the original data is recovered exactly.

What earns the marks

• State that RLE replaces a run of repeated consecutive values with a count and the value.
• Describe encoding by counting consecutive identical values and writing count then value.
• Describe decoding by repeating each value the number of times given by its count.
• Explain that RLE is effective when data contains long runs and less effective when values alternate.
• Recognise that RLE is lossless because the original data can be reconstructed exactly.

Common mistakes and how to put them right

• Counting non-consecutive repeats together.

  Put it right: RLE only groups values that are adjacent in the data.

• Claiming RLE always reduces file size.

  Put it right: Alternating data can grow because extra count values are added.

• Describing RLE as lossy.

  Put it right: RLE is lossless and restores the original exactly.

Exam tips

• Show a short worked example of encoding to demonstrate the count-then-value rule.
• State when RLE is suitable and when it is not, using the idea of long versus short runs.
• Mention that decoding reverses the process to recover the original data.