2023/12/28 by Xutan Peng, Peng, Xutan, Yi Zhang +5
Computer Science · #Advanced Data Compression Techniques #Algorithms and Data Compression #Data Structures and Algorithms (cs.DS) #Error Correcting Code Techniques #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Information Theory (cs.IT) #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2312.17024
openalex publication_date 2023/12/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Run-Length Encoding (RLE) is one of the most fundamental tools in data compression. However, its compression power drops significantly if there lacks consecutive elements in the sequence. In extreme cases, the output of the encoder may require more space than the input (aka size inflation). To alleviate this issue, using combinatorics, we quantify RLE's space savings for a given input distribution. With this insight, we develop the first algorithm that automatically identifies suitable symbols, then selectively encodes these symbols with RLE while directly storing the others without RLE. Through experiments on real-world datasets of various modalities, we empirically validate that our method, which maintains RLE's efficiency advantage, can effectively mitigate the size inflation dilemma.