Data Compression
📜 Abstract
Data compression codes (also known as source codes) and source coding algorithms are used to compress data: to represent data by fewer bits (and thus achieve lower data rates) than its original form. Different classes of codes and algorithms allow for different levels of compression, depending on the type of data and its requirements for quality. This paper surveys two main types of data compression: lossless and lossy compression. In lossless compression, the original data can be perfectly reconstructed from the compressed data. In contrast, lossy compression involves a loss of data, so that the original data cannot be perfectly reconstructed. Various compression techniques are discussed, including Huffman coding, arithmetic coding, the LZ77 and LZ78 algorithms, and various lossy transformation techniques like JPEG.
✨ Summary
The paper “Data Compression” authored by David Salomon and published in 1996 provides a comprehensive overview of both lossless and lossy data compression techniques. It examines well-known algorithms such as Huffman coding, arithmetic coding, and the LZ77 and LZ78 algorithms. Despite being published some time ago, the paper remains a useful reference for understanding fundamental data compression techniques. However, a quick search for direct citations or references in recent academic work yielded few explicit references to this text in contemporary scholarly articles, which implies its influence in more foundational areas or textbooks rather than active research. The lack of numerous explicit citations suggests that while it provides valuable foundational knowledge, it might not be a focal point in current cutting-edge research. Nevertheless, its discussions have likely contributed to the broader knowledge base from which newer algorithms and techniques have been developed, such as in software engineering and communication systems.