Run Length Encoding

Run-Length Encoding (RLE) is a simple compression algorithm used to represent consecutive repeated characters or values in a string or sequence as a single character followed by a count of the number of times it repeats.

This technique is often used in data compression, image compression, and various applications where reducing redundancy can save space.

RLE Text Compression

Text example

Consider the followng string.

AAABBBBCCCDDDDDDDDDFFAAAAAAAAAGGGG

This would be compressed as:

A3B4C3D9F2A9G4

• Original text length: 34 characters
• Compressed length: 14 characters
• Compression: 59% compression 

RLE Text Encoding Interactive Demonstration

Click on the grid below to see RLE text encoding in action.

B&W Image Compression

The B&W image above (part of a scanned hard-copy of a document) would be represented as:

14W5B8W2B2W3B6W2B4W2B5W2B5W2B4W2B6W2B3W2
B6W2B3W2B6W3B2W2B7W2B2W2B7W2B2W2B7W2B2W2
B7W2B2W2B6W3B2W2B6W2B3W2B5W3B3W2B5W2B4W2
B3W4B4W2B2W4B5W6B7W5B20W

• Compressed Data length: 144 Characters
• Original Data length: 273 Characters
• 57% Compression

RLE Bitmap Encoding Interactive Demonstration

Click on the grid below to see RLE in action.

Advantages of Run Length Encoding

Simplicity

RLE is extremely easy to understand and implement. It doesn't require complex algorithms or extensive computational resources.

Efficient for Repeated Data

RLE works exceptionally well when there are long runs of repeated characters or values in the data. It can achieve significant compression in such cases.(especially faxes and B&W scans of text documents)

Lossless Compression

RLE is a lossless compression technique, meaning it allows you to perfectly reconstruct the original data after decompression.

Fast Compression and Decompression

Due to its simplicity, RLE compression and decompression are very fast operations, making it suitable for real-time applications or scenarios where speed is critical.

Disadvantages of Run Length Encoding

Ineffective for Complex Data

RLE is not effective for data with little or no repetition. In such cases, it may even increase the size of the data due to the overhead of encoding.

Limited Applicability

RLE is primarily suited for specific types of data, such as simple binary images, bitmap graphics, and certain types of text data. It may not perform well for more diverse or random data.

Lack of Adaptive Compression

RLE doesn't adapt to changing patterns in the data. It treats each run independently, which can be inefficient for data with varying run lengths.

Not Suitable for Continuous Tonal Data

RLE is not suitable for continuous tonal data, such as audio or video, where there is a wide range of possible values for each sample.