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Data Compression is a category of books focused on the principles and practice of representing digital data more compactly to save storage and speed transmission. It spans foundational information theory (entropy, redundancy), classic lossless methods (Huffman, arithmetic, LZ/dictionary coding), and lossy techniques for images, audio, and video (transform coding, quantization, JPEG, MP3/AAC, H.264/AV1), alongside modern neural and learned compression. Titles range from textbooks and standards references to hands-on guides, covering algorithm design, implementation, and evaluation (compression ratio, rate–distortion), as well as trade-offs among speed, memory, quality, and energy. Aimed at students, researchers, and practitioners, these books connect theory to real-world formats, codecs, and tools used in filesystems, databases, networking, and media delivery.

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