Thursday, February 28, 2013 | 2:00 PM
By Lode Vandevenne, Software Engineer, Compression Team
Cross-posted with the Google Open Source Blog
The Zopfli Compression Algorithm is a new open sourced general purpose data compression library that got its name from a Swiss bread recipe. It is an implementation of the Deflate compression algorithm that creates a smaller output size compared to previous techniques. The smaller compressed size allows for better space utilization, faster data transmission, and lower web page load latencies. Furthermore, the smaller compressed size has additional benefits in mobile use, such as lower data transfer fees and reduced battery use. The higher data density is achieved by using more exhaustive compression techniques, which make the compression a lot slower, but do not affect the decompression speed. The exhaustive method is based on iterating entropy modeling and a shortest path search algorithm to find a low bit cost path through the graph of all possible deflate representations.
The output generated by Zopfli is typically 3–8% smaller compared to zlib at maximum compression, and we believe that Zopfli represents the state of the art in Deflate-compatible compression. Zopfli is written in C for portability. It is a compression-only library; existing software can decompress the data. Zopfli is bit-stream compatible with compression used in gzip, Zip, PNG, HTTP requests, and others.
Due to the amount of CPU time required — 2 to 3 orders of magnitude more than zlib at maximum quality — Zopfli is best suited for applications where data is compressed once and sent over a network many times, for example, static content for the web. By open sourcing Zopfli, thus allowing webmasters to better optimize the size of frequently accessed static content, we hope to make the Internet a bit faster for all of us.
Lode Vandevenne is a software engineer based in Zürich. He has a special interest in compression algorithms, and implemented Zopfli as his 20% time activity.
Posted by Scott Knaster, Editor