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Alex Allain has a nice article on the Huffman Compression Algorithm in case the Wiki doesn't suffice. On the other hand there are lossy algorithms too compromise accuracy to compress your data, but often works pretty well.

4. Huffman Coding with Example - Data Compression

State of the art lossy techniques combine ideas from differential coding, quantization, and DCT, among others. It is a very accessible introduction text. The 3rd edition out there in pdf online. There are an awful lot of data compression algorithms around. If you're looking for something encyclopedic, I recommend the Handbook of Data Compression by Salomon et al, which is about as comprehensive as you're likely to get and has good sections on the principles and practice of data compression, as well. My best guess is that ASIC-based compression is usually implemented for a particular application, or as a specialized element of a SoC, rather than as a stand-alone compression chip.

I also doubt that looking for a "latest and greatest" compression format is the way to go here -- I would expect standardization, maturity, and fitness for a particular purpose to be more important.

Handbook of Data Compression

My paper A Survey Of Architectural Approaches for Data Compression in Cache and Main Memory Systems permalink here reviews many compression algorithms and also techniques for using them in modern processors. LZW or Lempel Ziv algorithm is a great lossless one. Use Stack Overflow for Teams at work to find answers in a private and secure environment. Get your first 10 users free. Sign up. Learn more. First 10 Free. Data Compression Algorithms Ask Question.

Asked 6 years, 4 months ago. Active 1 year, 3 months ago. Viewed 59k times. If my question is too open ended, please let me know and I'll revise. Thank you. Veridian Veridian 1, 9 9 gold badges 31 31 silver badges 62 62 bronze badges.

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Handbook Of Data Compression by David Salomon

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