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Everything about Data compression

Compact encoding of digital data

In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Data compressionA 5-minute orientation
  2. Skim a recent paper: K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big dataInfluential work since 2022
  3. Pick up a classic book: Compressed video over networksThe most-reprinted book on the subject
  4. Read the landmark paper: Comprehensive Integration of Single-Cell DataCited 16,231 times
  5. Go sideways: Lossy compressionA closely related topic
  6. Go sideways: Video coding formatA closely related topic

📖 Definitions

Noun Any of several techniques for reducing the number of bits needed to represent an item of digital data, either to save storage or to use less bandwidth when transmitting it

🗂️ The subject at a glance

  1. Lossless
  2. Lossy
  3. Theory
  4. Uses
  5. Outlook and currently unused potential
  6. Data compression algorithms

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics