Effectiveness Analysis of Run-Length Encoding and Huffman Coding Combination in Digital Image Compression

The increasing use of digital images has led to a greater need for efficient data storage and transmission. This study aims to implement and analyze the effectiveness of the combination of Run-Length Encoding (RLE) and Huffman Coding in digital image compression based on Compression Ratio, Space Saving, processing time, and image integrity. The study uses an experimental method with a quantitative and implementative approach. The research population is two-dimensional digital images with a sample of 20 images, consisting of 10 RGB images and 10 grayscale images from Kaggle and DIV2K. The research instrument is a computer with a Python-based system, while the analysis is carried out quantitatively and descriptively through Black Box Testing and Performance Testing. The results of the study show that the compression and decompression processes were successful and the decompressed images remained intact. However, the size efficiency is not optimal. The RGB1 image produces a Compression Ratio of 0.177 and Space Saving of -464.84%, while RGB3 produces 0.0363 and -2654.78%. In conclusion, the combination of RLE and Huffman Coding is able to maintain image integrity, but is not yet effective in reducing file size in the tested samples.