Arithmetic Coding
Arithmetic coding is a lossless data compression technique that encodes a sequence of symbols into a single fractional number between 0 and 1, using probability distributions to represent more frequent symbols with fewer bits. It achieves near-optimal compression by assigning intervals to symbols based on their likelihood, allowing for efficient encoding of data streams like text, images, or audio. Unlike Huffman coding, it can handle fractional bits per symbol, making it particularly effective for compressing data with skewed or adaptive probability models.
Developers should learn arithmetic coding when working on data compression applications, such as file archiving (e.g., ZIP formats), multimedia codecs (e.g., JPEG, MPEG), or communication systems where bandwidth efficiency is critical. It is especially useful in scenarios with non-integer entropy or when dealing with large alphabets, as it outperforms simpler methods like Huffman coding by providing better compression ratios. Knowledge of arithmetic coding is also valuable for implementing adaptive compression algorithms that update symbol probabilities dynamically during encoding.